Professor Brett Ninness
Professor
School of Engineering (Electrical and Computer Engineering)
- Email:brett.ninness@newcastle.edu.au
- Phone:(02) 4921 7071
Career Summary
Biography
Brett Ninness began life in Singleton, Australia and received his BE, ME and Ph.D degrees in Electrical Engineering from the University of Newcastle, Australia, where he is currently appointed as Professor and has worked in Assistant Dean, Deputy Head of Faculty and Pro Vice Chancellor (Acting) roles.
His research interests are in the areas of dynamic system modelling, system identification, and stochastic signal processing, in which he has authored over a hundred papers. He has served on the editorial boards of Automatica, IEEE Transactions on Automatic Control and as Editor in Chief for IET Control Theory and Applications, and as a member of the Australian Research Council College of Experts. He has also served as chair of international committees, included the International Federation of Automatic Control (IFAC) Technical Committee on Modelling, Identification and Signal Processing and the Institute of Electrical and Electronic Engineers (IEEE) Technical Committee on System Identification and Adaptive Control.
Research ExpertiseMy research is concerned with the processing of noise corrupted signals. Within this theme, my home area is the science of System Identification which addresses the following problem. Given particular observations of the behaviour of a system, develop a mathematical model for it which can be used (for example) to control it via feedback, predict its performance under different operating regimes, compensate for limitations in its performance, or diagnose faults and changes in it. Recently, I have begun new research directions in the area of signal processing for wireless communications, largely via interaction with industry partners Bell Labs, Agere Systems and LSI Logic.
Teaching Expertise
My teaching experience over the last twenty years has covered a wide range of the electrical engineering and engineering mathematics curriculum. This includes the areas of systems and signal theory, signal processing, digital systems, embedded systems, circuit theory, communications and linear electronics.
Administrative Expertise
I have experience and hence expertise in School, Faculty and University wide governance. I served on the University promotions committee for three years, served as an Assistant Dean (Research Training) for my Faculty of three years, and am currently deputy head of faculty.
Collaborations
Royal Institute of Technology, Stockholm, Sweden Linköping University, Linköping, Sweden. Vrije Universiteit Brussel, Brussels Belgium
Qualifications
- PhD, University of Newcastle
- Bachelor of Engineering, University of Newcastle
- Master of Engineering, University of Newcastle
Keywords
- Automatic Control
- Circuit Theory
- Communications
- Digital Signal Processing
- Embedded Systems
- Linear Electronics
- Signal Processing
- Signals and Systems
- System Identification
- Wireless communications
Languages
- English (Fluent)
Fields of Research
Code | Description | Percentage |
---|---|---|
490105 | Dynamical systems in applications | 100 |
Professional Experience
UON Appointment
Title | Organisation / Department |
---|---|
Professor | University of Newcastle School of Electrical Engineering and Computing Australia |
Academic appointment
Dates | Title | Organisation / Department |
---|---|---|
1/1/2007 - | Chair - IEEE Technical Committee on Identification and Adaptive Control | Institution of Electrical and Electronic Engineers Australia |
1/9/2006 - | Editor in Chief | Institution of Engineering and Technology - Control Theory and Applications United Kingdom |
1/7/2005 - | Chair - IFAC Technical Committee on Modelling, Identification and Signal Processing | International Federation on Automatic Control Australia |
1/6/2004 - 1/4/2006 | Organising Chair - 14th IFAC Symposium on System Identification | International Federation on Automatic Control Australia |
1/1/2002 - | ARC Ozreader - Maths and IT RFCD | ARC (Australian Research Council) |
Membership
Dates | Title | Organisation / Department |
---|---|---|
Associate Editor - Automatica | Automatica Journal Australia |
|
Associate Editor - IEEE Transactions on Automatic Control | IEEE Transactions on Automatic Control Australia |
Awards
Distinction
Year | Award |
---|---|
2001 |
Tall Poppy Award Australian Institute of Policy & Science (AIPS) |
Publications
For publications that are currently unpublished or in-press, details are shown in italics.
Chapter (6 outputs)
Year | Citation | Altmetrics | Link | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
2011 |
Wills A, Ninness B, 'System identification of linear parameter varying state-space models', Linear Parameter-varying System Identification: New Developments And Trends 295-315 (2011) This chapter examines the estimation of multivariable linear models for which the parameters vary in a time-varying manner that depends in an affine fashion on a known or otherwis... [more] This chapter examines the estimation of multivariable linear models for which the parameters vary in a time-varying manner that depends in an affine fashion on a known or otherwise measured signal. These locally linear models which depend on a measurable operating point are known as linear parameter varying (LPV) models. The contribution here relative to previous work on the topic is that in the Gaussian case, an expectation-maximisation (EM) algorithm-based solution is derived and profiled.
|
||||||||||
2005 |
Van Den Hof P, Ninness BM, 'System Identification With Generalized Orthonormal Basis Functions', Modelling And Identification with Rational Orthogonal Basis Functions, Springer, Berlin 61-102 (2005) [B1]
|
||||||||||
2005 | Wahlberg B, Ninness BM, Van Den Hof P, 'Introduction', Modelling and Identification With Rational Orthogonal Basis Functions, Springer, Berlin 1-14 (2005) [B1] | ||||||||||
2005 |
Ninness BM, Hjalmarsson H, 'Variance Error, Reproducing Kernels, and Orthonormal Bases', Modelling and Identification with Rational Orthogonal Basis Functions, Springer, Berlin 103-159 (2005) [B1]
|
Nova | |||||||||
2005 | Ninness BM, Hjalmarsson H, 'Numerical Conditioning', Modelling and Identification with Rational Orthogonal Basis Functions, Springer, Berlin 161-211 (2005) [B1] | ||||||||||
2001 |
Weller SR, Moran W, Ninness BM, Pollington AD, 'Limiting zeros of sampled-data systems with first-order holds', Defence Applications of Signal Processing, Elsevier, Amsterdam, The Netherlands 272-277 (2001) [B1]
|
||||||||||
Show 3 more chapters |
Journal article (87 outputs)
Year | Citation | Altmetrics | Link | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
2024 |
Mehmood A, Raja MAZ, Ninness B, 'Design of fractional-order hammerstein control auto-regressive model for heat exchanger system identification: Treatise on fuzzy-evolutionary computing', Chaos, Solitons and Fractals, 181 (2024) [C1] Parameter estimation of nonlinear dynamical Hammerstein processes is a renowned stiff optimization problem with extensive applications in the design, robustness and stability anal... [more] Parameter estimation of nonlinear dynamical Hammerstein processes is a renowned stiff optimization problem with extensive applications in the design, robustness and stability analysis. Introduction of the fractional calculus theories and concepts further escalates the competency of accurate modelling of Hammerstein system but at the cost of increase in the stiffness of parameter estimation and complexity. This study deals with a presentation of new design of fractional-order nonlinear Hammerstein control auto-regressive (FO-NHCAR) model for heat exchanger system by introducing fractional derivative of polynomial based transformation operator in linear dynamic block. The system identification problem of FO-NHCAR heat exchanger system is constructed by exploiting approximation theory in mean squared error sense taken between the actual and estimated responses. Exhaustive simulations are conducted via well-known global search efficacy of the fuzzy-evolutionary computing paradigm i.e., fuzzy-genetic algorithms (GAs), for FO-NHCAR heat exchanger model by variation in signal to noise ratios, model's degrees of freedom, fractional orders, and Hammerstein kernels. The parameter vectors of FO-NHCAR models are identified consistently with the fuzzy-GAs for various noisy environments with negligible proximity error. Results comparison on rigorous statistical analysis further endorse the efficient, accurate, robust and stable performance of fuzzy- GAs for estimation of FO-NHCAR heat exchanger system parameters.
|
||||||||||
2023 |
Geng LH, Wills AG, Ninness B, Schon TB, 'Smoothed State Estimation via Efficient Solution of Linear Equations', IEEE Transactions on Automatic Control, 68 5877-5889 (2023) [C1] This article addresses the problem of computing fixed-interval smoothed state estimates of a linear time-varying Gaussian stochastic system. There already exist many algorithms th... [more] This article addresses the problem of computing fixed-interval smoothed state estimates of a linear time-varying Gaussian stochastic system. There already exist many algorithms that perform this computation, but all of them impose certain restrictions on system matrices in order for them to be applicable, and the restrictions vary considerably between the various existing algorithms. This article establishes a new sufficient condition for the fixed-interval smoothing density to exist in a Gaussian form that can be completely characterized by associated means and covariances. It then develops an algorithm to compute these means and covariances with no further assumptions required. This results in an algorithm more generally applicable than any one of the multitude of existing algorithms available to date.
|
Nova | |||||||||
2023 |
Courts J, Wills AG, Schön TB, Ninness B, 'Variational system identification for nonlinear state-space models', Automatica, 147 (2023) [C1] This paper considers parameter estimation for nonlinear state-space models, which is an important but challenging problem. We address this challenge by employing a variational inf... [more] This paper considers parameter estimation for nonlinear state-space models, which is an important but challenging problem. We address this challenge by employing a variational inference (VI) approach, which is a principled method that has deep connections to maximum likelihood estimation. This VI approach ultimately provides estimates of the model as solutions to an optimisation problem, which is deterministic, tractable and can be solved using standard optimisation tools. A specialisation of this approach for systems with additive Gaussian noise is also detailed. The proposed method is examined numerically on a range of simulated and real examples focusing on the robustness to parameter initialisation; additionally, favourable comparisons are performed against state-of-the-art alternatives.
|
Nova | |||||||||
2022 |
Hendriks JN, Holdsworth JRZ, Wills AG, Schon TB, Ninness B, 'Data to Controller for Nonlinear Systems: An Approximate Solution', IEEE Control Systems Letters, 6 1196-1201 (2022) [C1] This letter considers the problem of determining an optimal control action based on observed data. We formulate the problem assuming that the system can be modeled by a nonlinear ... [more] This letter considers the problem of determining an optimal control action based on observed data. We formulate the problem assuming that the system can be modeled by a nonlinear state-space model, but where the model parameters, state and future disturbances are not known and are treated as random variables. Central to our formulation is that the joint distribution of these unknown objects is conditioned on the observed data. Crucially, as new measurements become available, this joint distribution continues to evolve so that control decisions are made accounting for uncertainty as evidenced in the data. The resulting problem is intractable which we obviate by providing approximations that result in finite dimensional deterministic optimization problems. The proposed approach is demonstrated in simulation on a nonlinear system.
|
Nova | |||||||||
2022 |
Balenzuela MP, Wills AG, Renton C, Ninness B, 'A new smoothing algorithm for jump Markov linear systems', Automatica, 140 (2022) [C1] This paper presents a method for calculating the smoothed state distribution for Jump Markov Linear Systems. More specifically, the paper details a novel two-filter smoother that ... [more] This paper presents a method for calculating the smoothed state distribution for Jump Markov Linear Systems. More specifically, the paper details a novel two-filter smoother that provides closed-form expressions for the smoothed hybrid state distribution. This distribution can be expressed as a Gaussian mixture with a known, but exponentially increasing, number of Gaussian components as the time index increases. This is accompanied by exponential growth in memory and computational requirements, which rapidly becomes intractable. To ameliorate this, we limit the number of allowed mixture terms by employing a Gaussian likelihood mixture reduction strategy, which results in a computationally tractable, but approximate smoothed distribution. The approximation error can be balanced against computational complexity in order to provide an accurate and practical smoothing algorithm that compares favourably to existing state-of-the-art approaches.
|
Nova | |||||||||
2022 |
Balenzuela MP, Wills AG, Renton C, Ninness B, 'Parameter estimation for Jump Markov Linear Systems', Automatica, 135 (2022) [C1] Jump Markov linear systems (JMLS) are a useful model class for capturing abrupt changes in system behaviour that are temporally random, such as when a fault occurs. In many situat... [more] Jump Markov linear systems (JMLS) are a useful model class for capturing abrupt changes in system behaviour that are temporally random, such as when a fault occurs. In many situations, accurate knowledge of the model is not readily available and can be difficult to obtain based on first principles. This paper presents a method for learning parameter values of this model class based on available input¿output data using the maximum-likelihood framework. In particular, the expectation¿maximisation method is detailed for this model class with attention given to a deterministic and numerically stable implementation. The presented algorithm is compared to state-of-the-art methods on several simulation examples with favourable results.
|
Nova | |||||||||
2020 |
Eielsen AA, Leth J, Fleming AJ, Wills AG, Ninness B, 'Large-Amplitude Dithering Mitigates Glitches in Digital-to-Analogue Converters', IEEE Transactions on Signal Processing, 68 1950-1963 (2020) [C1]
|
Nova | |||||||||
2018 |
Marelli D, Zamani M, Fu M, Ninness B, 'Distributed Kalman filter in a network of linear systems', Systems and Control Letters, 116 71-77 (2018) [C1]
|
Nova | |||||||||
2015 |
Marelli D, Fu M, Ninness B, 'Asymptotic Optimality of the Maximum-Likelihood Kalman Filter for Bayesian Tracking with Multiple Nonlinear Sensors', IEEE Transactions on Signal Processing, 63 4502-4515 (2015) [C1] Bayesian tracking is a general technique for state estimation of nonlinear dynamic systems, but it suffers from the drawback of computational complexity. This paper is concerned w... [more] Bayesian tracking is a general technique for state estimation of nonlinear dynamic systems, but it suffers from the drawback of computational complexity. This paper is concerned with a class of Wiener systems with multiple nonlinear sensors. Such a system consists of a linear dynamic system followed by a set of static nonlinear measurements. We study a maximum-likelihood Kalman filtering (MLKF) technique which involves maximum-likelihood estimation of the nonlinear measurements followed by classical Kalman filtering. This technique permits a distributed implementation of the Bayesian tracker and guarantees the boundedness of the estimation error. The focus of this paper is to study the extent to which the MLKF technique approximates the theoretically optimal Bayesian tracker. We provide conditions to guarantee that this approximation becomes asymptotically exact as the number of sensors becomes large. Two case studies are analyzed in detail.
|
Nova | |||||||||
2013 |
Fleming AJ, Ninness B, Wills A, 'Recovering the spectrum of a low level signal from two noisy measurements using the cross power spectral density', Review of Scientific Instruments, 84 (2013) [C1]
|
Nova | |||||||||
2013 |
Ninness B, Wills A, Mills A, 'UNIT: A freely available system identification toolbox', Control Engineering Practice, 21 631-644 (2013) [C1]
|
Nova | |||||||||
2013 |
Wills A, Schön TB, Ljung L, Ninness B, 'Identification of Hammerstein-Wiener models', Automatica, 49 70-81 (2013) [C1] This paper develops and illustrates a new maximum-likelihood based method for the identification of Hammerstein-Wiener model structures. A central aspect is that a very general si... [more] This paper develops and illustrates a new maximum-likelihood based method for the identification of Hammerstein-Wiener model structures. A central aspect is that a very general situation is considered wherein multivariable data, non-invertible Hammerstein and Wiener nonlinearities, and colored stochastic disturbances both before and after the Wiener nonlinearity are all catered for. The method developed here addresses the blind Wiener estimation problem as a special case. © 2012 Elsevier Ltd. All rights reserved.
|
Nova | |||||||||
2012 |
Wills AG, Ninness BM, 'Generalised Hammerstein-Wiener system estimation and a benchmark application', Control Engineering Practice, 20 1097-1108 (2012) [C1]
|
Nova | |||||||||
2012 |
Wills AG, Knagge GS, Ninness BM, 'Fast linear model predictive control via custom integrated circuit architecture', IEEE Transactions on Control Systems Technology, 20 59-71 (2012) [C1]
|
Nova | |||||||||
2012 |
Mills AJ, Wills AG, Weller SR, Ninness BM, 'Implementation of linear model predictive control using a field-programmable gate array', IET Control Theory and Applications, 6 1042-1054 (2012) [C1]
|
Nova | |||||||||
2011 |
Schon TB, Wills AG, Ninness BM, 'System identification of nonlinear state-space models', Automatica, 47 39-49 (2011) [C1]
|
Nova | |||||||||
2010 |
Ninness BM, Wills AG, 'Discussion on: 'generalised linear dynamic factor models: An approach via singular autoregressions'', European Journal of Control, 16 225-227 (2010) [C3]
|
||||||||||
2010 |
Ninness BM, Henriksen SJ, 'Bayesian system identification via Markov chain Monte Carlo techniques', Automatica, 46 40-51 (2010) [C1]
|
||||||||||
2009 |
Knagge GS, Bickerstaff M, Ninness BM, Weller SR, Woodward G, 'A VLSI 8 x 8 MIMO Near-ML detector with preprocessing', Journal of Signal Processing Systems for Signal Image and Video Technology, 56 229-247 (2009) [C1]
|
Nova | |||||||||
2009 |
Wills AG, Ninness BM, Gibson S, 'Maximum likelihood estimation of state space models from frequency domain data', IEEE Transactions on Automatic Control, 54 19-33 (2009) [C1]
|
Nova | |||||||||
2008 |
Ninness BM, Henriksen SJ, 'Time-scale modification of speech signals', IEEE Transactions on Signal Processing, 56 1479-1488 (2008) [C1]
|
Nova | |||||||||
2008 |
Wills AG, Bates DR, Fleming AJ, Ninness BM, Moheimani SO, 'Model predictive control applied to constraint handling in active noise and vibration control', IEEE Transactions on Control Systems Technology, 16 3-12 (2008) [C1]
|
Nova | |||||||||
2008 |
Ninness BM, 'Editor', International Journal of Adaptive Control and Signal Processing, (2008) [C2]
|
||||||||||
2008 | Ninness BM, 'Associate Editor', Journal of Control Science and Engineering, (2008) [C2] | ||||||||||
2008 | Ninness BM, 'Editor-in-chief', IET Control Theory and Applications, (2008) [C2] | ||||||||||
2008 | Ninness BM, 'Associate Editor', Automatica, (2008) [C2] | ||||||||||
2008 |
Wills AG, Ninness BM, 'On gradient-based search for multivariable system estimates', IEEE Transactions on Automatic Control, 53 298-306 (2008) [C1]
|
Nova | |||||||||
2008 | Ninness BM, 'Associate Editor', IEEE Transactions on Automatic Control, (2008) [C2] | ||||||||||
2008 |
Henriksen SJ, Ninness BM, Weller SR, 'Convergence of Markov-chain Monte-Carlo approaches to multiuser and MIMO detection', IEEE Journal on Selected Areas in Communications, 26 497-505 (2008) [C1]
|
Nova | |||||||||
2007 |
Ninness BM, 'Editorial', IET Control Theory and Applications, 1 1 (2007) [C3]
|
||||||||||
2007 | Ninness BM, 'Editor-in-Chief', IET Control Theory and Applications, 1 (2007) [C2] | ||||||||||
2007 | Ninness BM, 'Associate Editor', Automatica, (2007) [C2] | ||||||||||
2007 | Ninness BM, 'Associate Editor', Journal of Control Science and Engineering, (2007) [C2] | ||||||||||
2007 | Ninness BM, 'Associate Editor', IEEE Transactions on Automatic Control, (2007) [C2] | ||||||||||
2006 |
Hjalmarsson H, Ninness BM, 'Least-squares estimation of a class of frequency functions: A finite sample variance expression', Automatica, 42 589-600 (2006) [C1]
|
||||||||||
2005 |
Ninness BM, Hjalmarsson H, 'Analysis of the variability of joint input-output estimation methods', Automatica, 41 1123-1132 (2005) [C1]
|
||||||||||
2005 |
Ninness BM, Hjalmarsson H, 'On the frequency domain accuracy of closed-loop estimates', Automatica, 41 1109-1122 (2005) [C1]
|
||||||||||
2005 |
Gibson S, Ninness BM, 'Robust maximum-likelihood estimation of multivariable dynamic systems', Automatica, 41 1667-1682 (2005) [C1]
|
Nova | |||||||||
2005 |
Gibson S, Wills AG, Ninness BM, 'Maximum-likelihood parameter estimation of bilinear systems', IEEE Transactions on Automatic Control, 50 1581-1596 (2005) [C1]
|
Nova | |||||||||
2005 |
Wills A, Ninness B, Gibson S, 'On gradient-based search for multivariable system estimates', IFAC Proceedings Volumes (IFAC-PapersOnline), 16 832-837 (2005) This paper addresses the design of gradient based search algorithms for multivariable system estimation. in particular, the work here considers so-called 'full parametrizatio... [more] This paper addresses the design of gradient based search algorithms for multivariable system estimation. in particular, the work here considers so-called 'full parametrization' approaches, and establishes that the recently developed 'Data Driven Local Coordinate' (DDLC) methods can be seen as a special case within a broader class of techniques that are designed to deal with rank-deficient Jacobians. This informs the design of a new algorithm that, via a strategy of dynamic Jacobian rank determination, is illustrated to offer enhanced performance. Copyright © 2005 IFAC.
|
||||||||||
2005 |
Ninness B, Wills A, Gibson S, 'The University of Newcastle identification toolbox (Unit)', IFAC Proceedings Volumes (IFAC-PapersOnline), 16 838-843 (2005) This paper describes a MATLAB-based software package for estimation of dynamic systems. A wide range of standard estimation approaches are sup- ported. These include the use of no... [more] This paper describes a MATLAB-based software package for estimation of dynamic systems. A wide range of standard estimation approaches are sup- ported. These include the use of non-parametric, subspace-based and prediction- error algorithms coupled (in the latter case) with either MIMO state space or MISO polynomial model structures. A key feature of the software is the implementation of several new techniques that have been investigated by the authors. These include the estimation of non-linear models, the use of non-standard model parametrizations, and the employment of Expectation Maximisation (EM) methods. Copyright © 2005 IFAC.
|
||||||||||
2005 |
Knagge G, Woodward G, Weller SR, Ninness B, 'A VLSI optimised parallel tree search for MIMO', 6TH AUSTRALIAN COMMUNICATIONS THEORY WORKSHOP 2005, PROCEEDINGS, 215-220 (2005)
|
||||||||||
2005 |
Henriksen S, Ninness B, Weller SR, 'Soft output multiuser detection via a Markov chain Monte Carlo approach', 6TH AUSTRALIAN COMMUNICATIONS THEORY WORKSHOP 2005, PROCEEDINGS, 229-235 (2005)
|
||||||||||
2004 |
Ninness BM, Hjalmarrsson H, 'The effect of regularization on variance error', IEEE transactions on Automatic Control, 49 1142-1147 (2004) [C1]
|
||||||||||
2004 |
Hjalmarsson H, Ninness B, 'An exact finite sample variance expression for a class of frequency function estimates', 2004 43RD IEEE CONFERENCE ON DECISION AND CONTROL (CDC), VOLS 1-5, 370-375 (2004)
|
||||||||||
2004 |
Ninness BM, Hjalmarsson H, 'Variance error quantifications that are exact for finite-model order', IEEE Transactions on Automatic Control, 49 1275-1291 (2004) [C1]
|
Nova | |||||||||
2004 |
Stoica P, Li J, Ninness BM, 'The waterbed effect in spectral estimation', IEEE Signal Processing Magazine, 21 88,100-89,100 (2004) [C1]
|
||||||||||
2004 |
Ninness BM, 'On the crlb for combined model and model-order estimation of stationary stochastic processes', IEEE Signal Processing Letters, 11 293-296 (2004) [C1]
|
||||||||||
2003 |
Ninness B, 'Robust control of identified models with mixed parametric and non-parametric uncertainties', EUROPEAN JOURNAL OF CONTROL, 9 381-383 (2003)
|
||||||||||
2003 |
Ninness BM, 'Discussion on: Robust Control of identified Models with Mixed Parametric and Non-Parametric Uncertainties', European Journal of Control, 9 381-383 (2003) [C1]
|
||||||||||
2003 |
Ninness BM, 'The Asymptotic CRLB for the Spectrum of ARMA Processes', IEEE Transactions on Signal Processing, 51 1520-1531 (2003) [C1]
|
||||||||||
2002 |
Bauer D, Ninness BM, 'Asymptotic properties of least-squares estimates of Hammerstein-Wiener models', International Journal of Control, 75 34-51 (2002) [C1]
|
||||||||||
2002 |
Ninness B, Henriksen S, Brinsmead T, 'System identification via a computational Bayesian approach', PROCEEDINGS OF THE 41ST IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-4, 1820-1825 (2002)
|
||||||||||
2002 |
Ninness BM, Gibson SH, 'Quantifying the accuracy of Hammerstein model estimation', Automatica, 38 2037-2051 (2002) [C1]
|
Nova | |||||||||
2001 |
Weller SR, Moran W, Ninness BM, Pollington AD, 'Sampling Zeros and the Euler-Frobenius Polynomials', IEEE Transactions of Automatic Control, 46 No. 2 340-343 (2001) [C1]
|
||||||||||
2001 |
Ninness BM, Hjalmarsson H, 'Model Structure and Numerical Properties of Normal Equations', IEEE Transactions on Circuits and Systems, 48 No. 4 425-437 (2001) [C1]
|
||||||||||
2000 |
Ninness BM, 'Strong Laws of Large Numbers Under Weak Assumptions with Applications', IEE Transactions on Automatic Control, 45, No 11 2117-2121 (2000) [C1]
|
||||||||||
1999 |
Ninness B, Hjalmarsson H, Gustafsson F, 'Generalized Fourier and Toeplitz results for rational orthonormal bases', SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 37 429-460 (1999) [C1]
|
||||||||||
1999 |
Ninness BM, Hjalmarsson H, Gustafsson F, 'The fundamental Role of General Orthonormal Bases in System Identification', IEEE Transactions on Automatic Control, 44 Number 7 1384-1406 (1999) [C1]
|
Nova | |||||||||
1999 |
Akcay H, Islam SM, Ninness BM, 'Subspace-Based Identification of Power Transformer Models from Frequency Response Data', IEEE Transactions on Instrumentation and Measurement, 48 700-704 (1999) [C1]
|
||||||||||
1999 |
Ninness B, 'Aspects of linear estimation in H infinty', International Journal of Control, 72 1402-1416 (1999) A recent but rapidly maturing field in the area of system identification has been that of ¿estimation in H infinty¿. Greatly influencing this work has been the phenomenon that no ... [more] A recent but rapidly maturing field in the area of system identification has been that of ¿estimation in H infinty¿. Greatly influencing this work has been the phenomenon that no linear (in-the-data) algorithm exists which is ¿robustly convergent¿. This paper conducts a study of this issue by combining specific new analysis together with existing results from the mathematics literature on the topic of polynomial approximation theory. Particular attention is paid to the role of model order, and this leads to the consideration of model order selection from a deterministic worst-case perspective. © 1999 Taylor and Francis Group, LLC.
|
||||||||||
1999 |
Ninness BM, 'Aspects of Linear Estimation in H(infinity)', International Journal of Control, 72, No. 5 1402-1416 (1999) [C1]
|
||||||||||
1999 |
Akcay H, Ninness BM, 'Orthonormal Basis Functions for Continuous-Time Systems and Lp-Convergence', Mathematics of Control, Signals and Systems, 12, No. 3 295-305 (1999) [C1]
|
||||||||||
1999 |
Akcay H, Ninness BM, 'Orthonormal Basis Functions for Modelling Continuous-Time Systems', IEEE Transactions on Signal Processing, 77 261-274 (1999) [C1]
|
||||||||||
1998 |
Akcay H, Islam SM, Ninness B, 'Identification of power transformer models from frequency response data: A case study', SIGNAL PROCESSING, 68 307-315 (1998)
|
||||||||||
1998 |
Akcay H, Islam SM, Ninness B, 'Subspace based identification of power transformer models from frequency response data', PROCEEDINGS OF THE 1998 AMERICAN CONTROL CONFERENCE, VOLS 1-6, 3398-3402 (1998)
|
||||||||||
1998 |
Akcay H, Ninness B, 'Rational basis functions for robust identification from frequency and time domain measurements', PROCEEDINGS OF THE 1998 AMERICAN CONTROL CONFERENCE, VOLS 1-6, 3559-3563 (1998)
|
||||||||||
1998 |
Akcay H, Ninness B, 'On the worst-case divergence of the least-squares algorithm', PROCEEDINGS OF THE 1998 AMERICAN CONTROL CONFERENCE, VOLS 1-6, 3566-3569 (1998)
|
||||||||||
1998 |
Ninness BM, 'A Stochastic Approach to Linear Estimation in H(infinity)*', Automatica, 34 405-414 (1998) [C1]
|
||||||||||
1998 |
Akcay H, Ninness BM, 'Rational Basis Functions for Robust Identification from Frequency and Time-Domain Measurements', Automatica, 34 1101-1117 (1998) [C1]
|
Nova | |||||||||
1998 |
Ninness BM, 'Estimation of 1/f Noise', IEEE Transactions on Information Theory, 44 32-46 (1998) [C1]
|
Nova | |||||||||
1998 |
Ninness BM, Gomez JC, 'Frequency Domain Analysis of Tracking and Noise Performance of Adaptive Algorithms', IEEE Transactions on Signal Processing, 46 1314-1332 (1998) [C1]
|
||||||||||
1998 |
Akcay H, Ninness BM, 'On the worst-case divergence of the least-squares algorithm', Systems and Control Letters, 33 19-24 (1998) [C1]
|
||||||||||
Show 84 more journal articles |
Conference (84 outputs)
Year | Citation | Altmetrics | Link | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
2023 |
Wills AG, Hendriks J, Renton C, Ninness B, 'A Numerically Robust Bayesian Filtering Algorithm for Gaussian Mixture Models', IFAC PAPERSONLINE, AUSTRALIA, Canberra (2023) [E1]
|
Nova | |||||||||
2021 |
Courts J, Hendriks J, Wills A, Schon TB, Ninness B, 'Variational State and Parameter Estimation', IFAC PAPERSONLINE, ITALY, Padova (2021) [E1]
|
Nova | |||||||||
2020 |
Geng LH, Ayele TB, Liu JC, Ninness B, 'Expectation Maximization Based FitzHugh-Nagumo Model Identification under Unknown Gaussian Measurement Noise', Proceedings of the 32nd Chinese Control and Decision Conference, CCDC 2020, Hefei, China (2020) [E1]
|
Nova | |||||||||
2018 |
Balenzuela MP, Dahlin J, Bartlett N, Wills AG, Renton C, Ninness B, 'Accurate Gaussian Mixture Model Smoothing using a Two-Filter Approach', 2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC), Miami Beach, FL (2018) [E1]
|
Nova | |||||||||
2018 |
Zamani M, Marelli D, Ninness B, Fu M, 'Distributed Estimation in Networks of Linear Time-invariant Systems', 2018 IEEE 14th International Conference on Control and Automation, ICCA, Anchorage, Alaska (2018) [E1]
|
Nova | |||||||||
2018 |
Dahlin J, Wills A, Ninness B, 'Sparse Bayesian ARX models with flexible noise distributions', IFAC-PapersOnLine. Proceedings of the 18th IFAC Symposium on System Identification SYSID 2018, Stockholm, Sweden (2018) [E1]
|
Nova | |||||||||
2018 |
Dahlin J, Wills A, Ninness B, 'Constructing Metropolis-Hastings proposals using damped BFGS updates', IFAC-PapersOnLine. Proceedings of the 18th IFAC Symposium on System Identification SYSID 2018, Stockholm, Sweden (2018) [E1]
|
Nova | |||||||||
2017 |
Geng LH, Ninness B, Wills A, Schön T, 'Smoothed State Estimation via Efficient Solution of Linear Equations', IFAC-PapersOnLine, Toulouse, France (2017) [E1]
|
Nova | |||||||||
2017 |
Bottegal G, Risuleo RS, Zamani M, Ninness B, Hjalmarsson H, 'On maximum likelihood identification of errors-in-variables models', IFAC-PapersOnLine, Toulouse, France (2017) [E1]
|
Nova | |||||||||
2016 |
Geng LH, Ninness B, 'Identification of nonlinear state-space models using joint state particle smoothing', Chinese Control Conference, CCC (2016) [E1] On the basis of a previous expectation maximization (EM) algorithm, this paper applies the particle Markov chain Monte Carlo (MCMC) technique to estimate nonlinear state-space mod... [more] On the basis of a previous expectation maximization (EM) algorithm, this paper applies the particle Markov chain Monte Carlo (MCMC) technique to estimate nonlinear state-space models (SSMs). The smoothed simultaneous particles for joint states are generated by importance resampling (IR) and are directly used to compute a log-likelihood function and its Jacobian vector and Hessian matrix. As a result, a relatively less computational load can thus be obtained, which is crucial to practical applications of the particle MCMC. In addition, the SSM parameters can be recursively iterated by the more efficient Newton method, in which an optimal step length for parameter update in each iteration is optimized by a 1-D search method. This presented identification method has a good global parameter convergence in case iteration parameters are initialized from quite large intervals of their respective true values. Finally, a numerical simulation for identification of a classical SSM is used to show the effectiveness of the studied identification method.
|
Nova | |||||||||
2016 |
Fleming AJ, Wills A, Ghalehbeygi OT, Routley B, Ninness B, 'A Nonlinear Programming Approach to Exposure Optimization in Scanning Laser Lithography', 2016 AMERICAN CONTROL CONFERENCE (ACC), Boston, MA (2016) [E1]
|
Nova | |||||||||
2016 |
Zamani M, Ninness B, Quevedo D, 'On the reachability property for networks of linear time-invariant subsystems', 2016 Australian Control Conference, AuCC 2016, Newcastle, NSW (2016) [E1]
|
Nova | |||||||||
2016 |
Zamani M, Khosravian A, Ninness B, 'Compensation of attacks on consensus networks', ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Shanghai, China (2016) [E1]
|
Nova | |||||||||
2015 |
Geng LH, Ninness B, Xia ZY, 'An improved square-root algorithm for RTS Kalman smoothing', 2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics (2015) [E1] This paper improves on a noted square-root RTS Kalman smoothing algorithm proposed by Park and Kailath for the application purpose. This improved square-root RTS algorithm is able... [more] This paper improves on a noted square-root RTS Kalman smoothing algorithm proposed by Park and Kailath for the application purpose. This improved square-root RTS algorithm is able to additionally accommodate arbitrary exogenous known input, as such case is quite common in the real-world applications. In addition, hyperbolic Householder transformations are employed to avoid the computation of the difference of two positive semi-definite matrices. The Givens rotations based unitary transformations are further used to make the resulting algorithm have higher computational efficiency. The relevant implementation steps of this algorithm is also addressed. Finally, a numerical simulation is given to verify this improved algorithm.
|
Nova | |||||||||
2015 |
Tran KT, Ninness B, 'Reunderstanding slice sampling as parallel MCMC', 2015 IEEE Conference on Control and Applications, CCA 2015 - Proceedings (2015) [E1] A robust slice sampler, which guarantees no repeated samples, is found as a special case of Metropolis sampling that can interact with parallel chains to efficiently sample from m... [more] A robust slice sampler, which guarantees no repeated samples, is found as a special case of Metropolis sampling that can interact with parallel chains to efficiently sample from multi-modal densities even with possibly isolated support sets. The algorithm is completely automated with no tuning required. Implications to particle filtering design for on-line state and parameter joint estimation is also discussed.
|
Nova | |||||||||
2015 |
Tran KT, Ninness B, 'Parallel MCMC algorithm for Bayesian system identification', Proceedings of the IEEE Conference on Decision and Control (2015) [E1] A generalised framework for Metropolis-Hastings admits many algorithms as specialisations and allows for synthesis of multiple methods to create a parallel algorithm, with no tuni... [more] A generalised framework for Metropolis-Hastings admits many algorithms as specialisations and allows for synthesis of multiple methods to create a parallel algorithm, with no tuning required, to efficiently draw uncorrelated samples, from the posterior density in Bayesian systems identification, at lower computational cost in comparison with conventional samplers. Two automatic annealing schemes demonstrate complementary robustness in detecting multi-modal distribution.
|
Nova | |||||||||
2015 |
Zamani M, Ninness B, Agüero JC, 'On Identification of Networked Systems with Time-invariant Topology', IFAC-PapersOnLine, Beijing, China (2015) [E1]
|
Nova | |||||||||
2015 |
Marelli D, Ninness B, Fu M, 'Distributed Weighted Least-Squares Estimation for Power Networks', IFAC-PapersOnLine, Beijing, China (2015) [E1]
|
Nova | |||||||||
2014 |
Weller SR, Schulz BP, Ninness BM, 'Identification of linear climate models from the CMIP3 multimodel ensemble', Proceedings of the 19th IFAC World Congress, 2014, Cape Town, South Africa (2014) [E1]
|
Nova | |||||||||
2014 |
Ninness B, Tran KT, Kellett CM, 'Bayesian Dynamic System Estimation', Proceedings of the 53rd IEEE Conference on Decision and Control, Los Angeles, California, USA (2014) [E1]
|
Nova | |||||||||
2014 |
Godoy BI, Valenzuela PE, Rojas CR, Aguero JC, Ninness B, 'A novel input design approach for systems with quantized output data', 2014 European Control Conference, ECC 2014, Strasbourg, France (2014) [E1]
|
Nova | |||||||||
2014 |
Knagge G, Wills A, Mills A, Ninness B, 'ASIC and FPGA implementation strategies for Model Predictive Control', 2009 European Control Conference, ECC 2009 (2014) [E1] This paper considers the system architecture and design issues for implementation of on-line Model Predictive Control (MPC) in Field Programmable Gate Arrays (FPGAs) and Applicati... [more] This paper considers the system architecture and design issues for implementation of on-line Model Predictive Control (MPC) in Field Programmable Gate Arrays (FPGAs) and Application Specific Integrated Circuits (ASICs). In particular, the computationally itensive tasks of fast matrix QR factorisation, and subsequent sequential quadratic programming, are addressed for control law computation. An important aspect of this work is the study of appropriate data word-lengths for various essential stages of the overall solution strategy.
|
Nova | |||||||||
2013 |
Fleming AJ, Ninness B, Wills AG, 'Spectral Estimation using Dual Sensors with Uncorrelated Noise', 2013 IEEE SENSORS, Baltimore, MD (2013) [E2]
|
||||||||||
2012 |
Wills AG, Schon TB, Lindsten F, Ninness BM, 'Estimation of linear systems using a Gibbs sampler', Proceedings 16th IFAC Symposium on System Identification, Bruxelles, Belgium (2012) [E1]
|
Nova | |||||||||
2012 |
Henriksen SJ, Wills AG, Schon TB, Ninness BM, 'Parallel implementation of particle MCMC methods on a GPU', Proceedings 16th IFAC Symposium on System Identification, Bruxelles, Belgium (2012) [E1]
|
Nova | |||||||||
2011 |
Wills AG, Mills AJ, Ninness BM, 'FPGA implementation of an interior-point solution for linear model predictive control', Proceedings of the 18th IFAC World Congress 2011, Milano, Italy (2011) [E1]
|
||||||||||
2011 |
Wills AG, Schon TB, Ljung L, Ninness BM, 'Blind identification of Wiener models', Proceedings of the 18th IFAC World Congress, 2011, Milano, Italy (2011) [E1]
|
||||||||||
2010 |
Ninness BM, Wills AG, Schon TB, 'Estimation of general nonlinear state-space systems', Proceedings of the 49th IEEE Conference on Decision and Control, Atlanta, GA (2010) [E1]
|
Nova | |||||||||
2010 |
Wills AG, Schon TB, Ninness BM, 'Estimating state-space models in innovations form using the expectation maximisation algorithm', Proceedings of the 49th IEEE Conference on Decision and Control, Atlanta, GA (2010) [E1]
|
Nova | |||||||||
2009 |
Ninness BM, 'Some system identification challenges and approaches', Proceedings of the 15th IFAC Symposium on System Identification, Saint-Malo, France (2009) [E1]
|
Nova | |||||||||
2009 |
Wills AG, Ninness BM, 'Estimation of generalised Hammerstein-Wiener systems', Proceedings of the 15th IFAC Symposium on System Identification, Saint-Malo, France (2009) [E1]
|
Nova | |||||||||
2009 |
Wills AG, Mills AJ, Ninness BM, 'A MATLAB software environment for system identification', Proceedings of the 15th IFAC Symposium on System Identification, Saint-Malo, France (2009) [E1]
|
Nova | |||||||||
2009 |
Mills AJ, Wills AG, Ninness BM, 'Nonlinear model predictive control of an inverted pendulum', Proceedings of the American Control Conference, St Louis, MO (2009) [E1]
|
Nova | |||||||||
2008 |
Wills AG, Schon TB, Ninness BM, 'Parameter estimation for discrete-time nonlinear systems using EM', Proceedings of the 17th World Congress of the International Federation of Automatic Control, Seoul, Korea (2008) [E1]
|
Nova | |||||||||
2008 |
Bates DR, Henriksen SJ, Ninness BM, Weller SR, 'A 4 x 4 FPGA-based wireless testbed for LTE applications', 19th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications 2008, Cannes, France (2008) [E1]
|
||||||||||
2007 |
Ninness BM, Wills AG, 'An Identification Toolbox for Profiling Novel Techniques', Preprints of the 14th IFAC Symposium on System Identification, Newcastle, Australia (2007) [E1]
|
||||||||||
2007 |
Schon TB, Wills AG, Ninness BM, 'Maximum Likelihood Nonlinear System Estimation', Preprints of the 14th IFAC Symposium on System Identification, Newcastle, Australia (2007) [E1]
|
||||||||||
2007 |
Schon TB, Wills AG, Ninness BM, 'Proccedings of the 14Tth IFAC Symposium on system identification', Preprints of the 14th IFAC Symposium on System Identification, Newcastle, Australia (2007) [E1]
|
||||||||||
2007 |
Wills AG, Ninness BM, Gibson S, 'Maximum likelihood estimation of state space models from frequency domain data', Proceedings of the European Control Conference 2007, Kos, Greece (2007) [E1]
|
||||||||||
2006 |
Wills AG, Ninness BM, Gibson SH, 'On Gradient-Based Search For Multivariable System Estimates', Proceedings of 16th IFAC World Congress, Prague, Czech Republic (2006) [E1]
|
||||||||||
2006 |
Ninness BM, Wills AG, Gibson SH, 'The University of Newcastle Identification ToolBox', Proceedings of The 16th IFAC World Congress, Prague, Czech Republic (2006) [E1]
|
||||||||||
2006 |
Knagge GS, Bickerstaff M, Ninness BM, Weller SR, Woodward G, 'A VLSI 8x8 MIMO Near-ML Decoder Engine', IEEE Workshop on Signal Processing Systems Design and Implementation, Banff, Alberta, Canada (2006) [E1]
|
||||||||||
2005 |
Knagge GS, Woodward GK, Weller SR, Ninness BM, 'A VLSI Optimised Parallel Tree Search For MIMO', Proceedings 6th Australian Communications Theory Workshop 2005 : 2-4 February 2005, The University of Queensland, Brisbane, Australia, Brisbane, QLD (2005) [E1]
|
||||||||||
2005 |
Henriksen SJ, Ninness BM, Weller SR, 'Soft Output Multiuser Detection Via A Markov Chain Monte Carlo Approach', Proceedings 6th Australian Communications Theory Workshop 2005 : 2-4 February 2005, The University of Queensland, Brisbane, Australia, Brisbane, QLD (2005) [E1]
|
||||||||||
2005 |
Wills AG, Bates DR, Fleming AJ, Ninness BM, Moheimani SO, 'Application of MPC to an Active Structure Using Sampling Rates up To 25kHz', Proceedings of the 44th IEEE Conference On Decision And Control, Seville, Spain (2005) [E1]
|
||||||||||
2004 | Ninness BM, 'Closed form frequency domain expressions for best achievable accuracy of spectral density estimation', CD-ROM, Montreal (2004) [E1] | ||||||||||
2004 |
Knagge GS, Woodward G, Weller SR, Ninness BM, 'An optimised parallel tree search for multiuser detection with vlsi implementation strategy', CD ROM, Dallas (2004) [E1]
|
||||||||||
2003 | Ninness BM, Henriksen SJ, 'System Identification via a Computational Bayesian Approach', Proceedings for IFAC SYSID 2003, Rotterdam, The Netherlands (2003) [E1] | ||||||||||
2003 |
Ninness B, Henriksen S, 'System identification via a computational Bayesian approach', IFAC Proceedings Volumes (IFAC-PapersOnline) (2003) This paper takes a Bayesian approach to the problem of dynamic system estimation, and illustrates how posterior densities for system parameters, or more abstract and rather arbitr... [more] This paper takes a Bayesian approach to the problem of dynamic system estimation, and illustrates how posterior densities for system parameters, or more abstract and rather arbitrary system properties (such a frequency response, phase margin etc.) may be numerically computed. In achieving this, the key idea of constructing an ergodic Markov chain with invariant distribution equal to the desired posterior is fundamental, and it is inspired by recent developments in the mathematical statistics literature. An essential point of the work here is that via the associated posterior computation from the Markov chain, error bounds on estimates are provided that do not rely on asymptotic in data length arguments, and hence they apply with arbitrary accuracy for arbitrarily short data records.
|
||||||||||
2003 |
Ninness BM, Hjalmarsson H, 'Variance Error Quantifications that are Exact for Finite Model Order', Proceedings for CDC 2003 (CD ROM), Maui, Hawaii, USA (2003) [E1]
|
||||||||||
2003 |
Ninness BM, Hjalmarsson H, 'On the Frequency Domain Accuracy of Closed Loop Estimates', Proceedings for CDC 2003 (CD ROM), Maui, Hawaii (2003) [E1]
|
||||||||||
2002 |
Gibson SH, Ninness BM, 'Maximum Likelihood Identification of Bilinear Systems', 15th Triennial World Congress, Barcelona, Spain (2002) [E1]
|
||||||||||
2002 |
Ninness BM, Hjalmarsson H, 'Accurate Quantification of Variance Error', 15th Triennial World Congress, Barcelona, Spain (2002) [E1]
|
||||||||||
2002 |
Ninness BM, Hjalmarsson H, 'Exact Quantification of Variance Error', 15th Triennial World Congress, Barcelona, Spain (2002) [E1]
|
||||||||||
2002 |
Ninness BM, Gibson SH, 'Robust and Simple Algorithms for Maximum Likelihood Estimation of Multivariable Systems', 15th Triennial World Congress, Barcelona, Spain (2002) [E1]
|
||||||||||
2001 | Ninness BM, Gibson SH, 'The EM Algorithm for Multivariable Dynamic System Estimation', IFAC Workshop on Adaptation and Learningin Control and Signal Processing, Cernobbio-Como, Italy (2001) [E2] | ||||||||||
2000 | Ninness BM, Hjalmarsson H, 'Improved and Quantified Accuracy for Linear Spectral Estimates', AS-SPCC 2000, Canada (2000) [E2] | ||||||||||
2000 |
Bauer D, Ninness BM, 'Asymptotic properties of Hammerstein model estimates', CDC Downunder, Sydney, Australia (2000) [E1]
|
||||||||||
2000 |
Gibson SH, Ninness BM, 'The Relationship between State Space Subspace Identification Methods and the EM Method', CDC Downunder, Sydney, Australia (2000) [E1]
|
||||||||||
2000 |
Ninness BM, Weller SR, 'Performance aspects of linear multiuser receivers', Globecom'00, San Francisco, USA (2000) [E1]
|
||||||||||
2000 |
Ninness BM, Henriksen S, 'Time and Frequency Scale Modification of Speech Signals', Silver Anniversary ICASSP 2000 Instanbul, Istanbul, Turkey (2000) [E1]
|
||||||||||
2000 |
Ninness BM, Gibson SH, Weller SR, 'Practical Aspects of using Orthonormal System Parameterisations in Estimation Problems', Symposium on System Identification Proceedings (CD-Rom), California, USA (2000) [E1]
|
||||||||||
2000 | Ninness BM, Gibson SH, 'Quantifying the Accuracy of Hammerstein Model Estimation', Symposium on System Identification Proceedings (CD-Rom), California, USA (2000) [E1] | ||||||||||
2000 | Van Den Hof P, Wahlberg B, Heuberger P, Ninness BM, Bokor J, Oliveira E Silva T, 'Modelling and Identification with Rational Orthogonal Basis Functions', Symposium on System Identification Proceedings (CD-Rom), California, USA (2000) [E1] | ||||||||||
1999 | Akcay H, Ninness BM, 'Orthonormal Basis Functions for Continuous-Time Systems: Completeness and L(subscrip)p - Convergence', European Control Conference ECC'99 - Conference Proceedings, Karlsruhe, Germany (1999) [E1] | ||||||||||
1999 | Ninness BM, Hjalmarsson H, 'Signal Spectra and Conditioning when using Orthonormal Parameterisation', European Control Conference ECC'99 - Conference Proceedings, Karlsruhe, Germany (1999) [E1] | ||||||||||
1999 | Ninness BM, Hjalmarsson H, 'Model Structure and Numerical Properties of Normal Equations', IFAC World Congress 1999, Beijing, P.R. China (1999) [E1] | ||||||||||
1999 | Hjalmarsson H, Gustafsson F, Ninness BM, 'Asymptotic Variance Expressions for Output Error Model Structures', IFAC World Congress 1999, Beijing, P.R. China (1999) [E1] | ||||||||||
1999 | Ninness BM, Hjalmarsson H, Gustafsson F, 'Estimation Variance is not Model Structure Independent', The 7th Mediterranean Conference on Control and Automation, Haifa, Israel (1999) [E1] | ||||||||||
1998 | Ninness B, Gomez JC, Weller S, 'Frequency domain analysis of adaptive tracking algorithms', (SYSID'97): SYSTEM IDENTIFICATION, VOLS 1-3, KITAKYUSHU, JAPAN (1998) | ||||||||||
1998 |
Hjalmarsson H, Ninness B, 'Identification in closed loop: Asymptotic high order variance for restricted complexity models', PROCEEDINGS OF THE 37TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-4, TAMPA, FL (1998)
|
||||||||||
1998 | Ninness B, Gomez JC, 'Quantifying the accuracy of adaptive tracking algorithms', PROCEEDINGS OF THE 1998 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-6, SEATTLE, WA (1998) | ||||||||||
1998 |
Hjalmarsson H, Ninness B, 'Fast, non-iterative estimation of Hidden Markov models', PROCEEDINGS OF THE 1998 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-6, SEATTLE, WA (1998)
|
||||||||||
Show 81 more conferences |
Grants and Funding
Summary
Number of grants | 36 |
---|---|
Total funding | $5,167,730 |
Click on a grant title below to expand the full details for that specific grant.
20141 grants / $488,531
Estimation of Complex Networked Dynamic Systems$488,531
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Brett Ninness |
Scheme | Discovery Projects |
Role | Lead |
Funding Start | 2014 |
Funding Finish | 2016 |
GNo | G1300431 |
Type Of Funding | Aust Competitive - Commonwealth |
Category | 1CS |
UON | Y |
20132 grants / $381,748
A novel framework for designing input excitation for system identification$361,748
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Associate Professor Kaushik Mahata, Professor Brett Ninness |
Scheme | Discovery Projects |
Role | Investigator |
Funding Start | 2013 |
Funding Finish | 2015 |
GNo | G1200242 |
Type Of Funding | Aust Competitive - Commonwealth |
Category | 1CS |
UON | Y |
New System Identification and Estimation Methods using Convex Relaxation Techniques$20,000
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Brett Ninness |
Scheme | Near Miss Grant |
Role | Lead |
Funding Start | 2013 |
Funding Finish | 2013 |
GNo | G1300462 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
20111 grants / $106,447
Multicore Computing of Advanced Engine Control Algorithms$106,447
Funding body: General Motors, USA.
Funding body | General Motors, USA. |
---|---|
Project Team | Professor Brett Ninness, Associate Professor Adrian Wills |
Scheme | Research Grant |
Role | Lead |
Funding Start | 2011 |
Funding Finish | 2011 |
GNo | G1000979 |
Type Of Funding | International - Non Competitive |
Category | 3IFB |
UON | Y |
20102 grants / $500,000
System Identification of Complex System Models$330,000
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Brett Ninness |
Scheme | Discovery Projects |
Role | Lead |
Funding Start | 2010 |
Funding Finish | 2012 |
GNo | G0190055 |
Type Of Funding | Aust Competitive - Commonwealth |
Category | 1CS |
UON | Y |
New Model Predictive Control Design Methods$170,000
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Brett Ninness, Professor Steven Weller |
Scheme | Discovery Projects |
Role | Lead |
Funding Start | 2010 |
Funding Finish | 2012 |
GNo | G0190095 |
Type Of Funding | Aust Competitive - Commonwealth |
Category | 1CS |
UON | Y |
20091 grants / $20,000
Fast and Robust Model Predictive Control$20,000
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Associate Professor Adrian Wills, Professor Brett Ninness, Doctor Geoffrey Knagge |
Scheme | Near Miss Grant |
Role | Investigator |
Funding Start | 2009 |
Funding Finish | 2009 |
GNo | G0189828 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
20081 grants / $15,000
Advanced nonlinear constrained control$15,000
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Associate Professor Adrian Wills, Professor Brett Ninness |
Scheme | Pilot Grant |
Role | Investigator |
Funding Start | 2008 |
Funding Finish | 2008 |
GNo | G0189105 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
20071 grants / $246,090
Advancing System Identification using Modern Optimisation Methods$246,090
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Brett Ninness, Associate Professor Adrian Wills |
Scheme | Discovery Projects |
Role | Lead |
Funding Start | 2007 |
Funding Finish | 2009 |
GNo | G0186347 |
Type Of Funding | Aust Competitive - Commonwealth |
Category | 1CS |
UON | Y |
20062 grants / $885,282
PRC - Priority Research Centre for Energy$549,282
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Conjoint Professor Bogdan Dlugogorski, Laureate Professor Behdad Moghtaderi, Emeritus Professor Robert Antonia, Prof LYAZID Djenidi, Associate Professor Jose De Dona, Professor Eric Kennedy, Associate Professor John Lucas, Conjoint Professor John Mackie, Emeritus Professor Marcel Maeder, Professor Brett Ninness, Emeritus Professor Adrian Page, Associate Professor Marian Radny, Associate Professor Phillip Smith, Professor Edward Szczerbicki, Emeritus Professor Terry Wall |
Scheme | Priority Research Centre |
Role | Investigator |
Funding Start | 2006 |
Funding Finish | 2013 |
GNo | G0186921 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
New Approaches for the Estimation of Complex Dynamic System Models$336,000
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Brett Ninness |
Scheme | Discovery Projects |
Role | Lead |
Funding Start | 2006 |
Funding Finish | 2008 |
GNo | G0185319 |
Type Of Funding | Aust Competitive - Commonwealth |
Category | 1CS |
UON | Y |
20054 grants / $1,029,933
New Methods and Microelectronics for Wireless Communication Systems$720,000
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Brett Ninness, Professor Steven Weller, Dr Graeme Woodward, Dr Mark Bickerstaff, Dr Adriel Kind, Dr L Davis |
Scheme | Linkage Projects |
Role | Lead |
Funding Start | 2005 |
Funding Finish | 2009 |
GNo | G0184265 |
Type Of Funding | Aust Competitive - Commonwealth |
Category | 1CS |
UON | Y |
New methods and microelectronics for wireless communication systems$250,000
Funding body: Agere Systems Australia Pty Ltd
Funding body | Agere Systems Australia Pty Ltd |
---|---|
Project Team | Professor Brett Ninness, Professor Steven Weller |
Scheme | Linkage Projects Partner Funding |
Role | Lead |
Funding Start | 2005 |
Funding Finish | 2009 |
GNo | G0185973 |
Type Of Funding | Contract - Aust Non Government |
Category | 3AFC |
UON | Y |
Australian Communications Research Network (ACoRN)$50,000
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Steven Weller, Professor Brett Ninness, Professor Sarah Johnson |
Scheme | Research Networks |
Role | Investigator |
Funding Start | 2005 |
Funding Finish | 2009 |
GNo | G0186088 |
Type Of Funding | Scheme excluded from IGS |
Category | EXCL |
UON | Y |
System Identification and Diagnosis via Markov Chain Monte Carlo Methods$9,933
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Brett Ninness |
Scheme | Project Grant |
Role | Lead |
Funding Start | 2005 |
Funding Finish | 2005 |
GNo | G0184665 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
20031 grants / $176,497
Robust Control and System Identification of Highly Resonant Systems.$176,497
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Reza Moheimani, Professor Brett Ninness |
Scheme | Discovery Projects |
Role | Investigator |
Funding Start | 2003 |
Funding Finish | 2005 |
GNo | G0182060 |
Type Of Funding | Aust Competitive - Commonwealth |
Category | 1CS |
UON | Y |
20023 grants / $629,285
New Methods for Dynamic System Estimation$360,000
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Brett Ninness |
Scheme | Discovery Projects |
Role | Lead |
Funding Start | 2002 |
Funding Finish | 2005 |
GNo | G0181106 |
Type Of Funding | Aust Competitive - Commonwealth |
Category | 1CS |
UON | Y |
Advanced Space-Time Coded Multiuser Wireless Communications via Test-bed Development$194,285
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Brett Ninness, Professor Steven Weller, Dr C Nicol, Dr L Davis |
Scheme | Linkage Projects |
Role | Lead |
Funding Start | 2002 |
Funding Finish | 2004 |
GNo | G0181156 |
Type Of Funding | Aust Competitive - Commonwealth |
Category | 1CS |
UON | Y |
Advanced Space-Time Coded Multiuser Wireless Communications via Test-bed Development.$75,000
Funding body: Lucent Technologies Australia Pty Ltd.
Funding body | Lucent Technologies Australia Pty Ltd. |
---|---|
Project Team | Professor Brett Ninness, Professor Steven Weller, Dr C Nicol, Dr L Davis |
Scheme | Linkage Projects Partner Funding |
Role | Lead |
Funding Start | 2002 |
Funding Finish | 2004 |
GNo | G0181879 |
Type Of Funding | Contract - Aust Non Government |
Category | 3AFC |
UON | Y |
20011 grants / $14,000
Development of a Space-Time coded Wireless Local Area Network$14,000
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Steven Weller, Professor Brett Ninness |
Scheme | Project Grant |
Role | Investigator |
Funding Start | 2001 |
Funding Finish | 2001 |
GNo | G0179970 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
20003 grants / $248,400
Applications of Advanced Control to Materials Rolling$186,000
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Brett Ninness, Emeritus Laureate Professor Graham Goodwin |
Scheme | Strategic Partnerships with Industry - Research & Training Scheme (SPIRT) |
Role | Lead |
Funding Start | 2000 |
Funding Finish | 2002 |
GNo | G0178641 |
Type Of Funding | Aust Competitive - Commonwealth |
Category | 1CS |
UON | Y |
Applications of Advanced Control to Materials Rolling.$60,000
Funding body: Industrial Automation Services
Funding body | Industrial Automation Services |
---|---|
Project Team | Professor Brett Ninness |
Scheme | SPIRT Partner Funding |
Role | Lead |
Funding Start | 2000 |
Funding Finish | 2002 |
GNo | G0181570 |
Type Of Funding | Contract - Aust Non Government |
Category | 3AFC |
UON | Y |
IFAC International Symposium on System Identification.$2,400
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Brett Ninness |
Scheme | Travel Grant |
Role | Lead |
Funding Start | 2000 |
Funding Finish | 2000 |
GNo | G0180265 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
19993 grants / $198,740
System Identification of Nonlinear Dynamic Systems for Closed Loop Control Applications$176,240
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Brett Ninness |
Scheme | Large Grant |
Role | Lead |
Funding Start | 1999 |
Funding Finish | 2001 |
GNo | G0177795 |
Type Of Funding | Aust Competitive - Commonwealth |
Category | 1CS |
UON | Y |
Nonlinear Identification and Control via Pilot Plant Experimentation.$11,500
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Brett Ninness |
Scheme | Project Grant |
Role | Lead |
Funding Start | 1999 |
Funding Finish | 1999 |
GNo | G0178097 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
Signature Set Design for Code-Division Multiple Access Communications.$11,000
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Steven Weller, Professor Brett Ninness |
Scheme | Project Grant |
Role | Investigator |
Funding Start | 1999 |
Funding Finish | 1999 |
GNo | G0178106 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
19981 grants / $2,400
Mathematical Theory of Networks and Systems, Italy 6-10 July 1998$2,400
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Brett Ninness |
Scheme | Travel Grant |
Role | Lead |
Funding Start | 1998 |
Funding Finish | 1998 |
GNo | G0180371 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
19963 grants / $99,400
EXAMINATION OF THE USE OF ORTHONORMAL BASIS FUNCTIONS IN SYSTEM IDENTIFICATION$90,000
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Brett Ninness |
Scheme | Large Grant |
Role | Lead |
Funding Start | 1996 |
Funding Finish | 1998 |
GNo | G0175249 |
Type Of Funding | Aust Competitive - Commonwealth |
Category | 1CS |
UON | Y |
Development of improved methods for estimation of audio signals for applications in speech compression and recognition.$7,000
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Brett Ninness, Dr Salvatore Crisafulli |
Scheme | Small Grant |
Role | Lead |
Funding Start | 1996 |
Funding Finish | 1996 |
GNo | G0175657 |
Type Of Funding | Scheme excluded from IGS |
Category | EXCL |
UON | Y |
International Federation of the Automatic Control World Congress - San Fransisco$2,400
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Brett Ninness |
Scheme | Travel Grant |
Role | Lead |
Funding Start | 1996 |
Funding Finish | 1996 |
GNo | G0176347 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
19951 grants / $2,500
European Control Conference (Rome) - 22-25 August 1995$2,500
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Brett Ninness |
Scheme | Travel Grant |
Role | Lead |
Funding Start | 1995 |
Funding Finish | 1995 |
GNo | G0175625 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
19943 grants / $111,177
Analysis of the Interplay between system identification and robust controller design$102,677
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Brett Ninness |
Scheme | Large Grant |
Role | Lead |
Funding Start | 1994 |
Funding Finish | 1996 |
GNo | G0175453 |
Type Of Funding | Aust Competitive - Commonwealth |
Category | 1CS |
UON | Y |
Speech coding and reconstruction for the purposes of arbitrary time scale modification, pitch modification and data compression.$6,000
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Brett Ninness |
Scheme | Project Grant |
Role | Lead |
Funding Start | 1994 |
Funding Finish | 1994 |
GNo | G0174761 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
10th IFAC Symposium on system Identification & Annual Baltimore/Copenhagen American Control Conference - 29 June-1 July & 4-6 July 1994$2,500
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Brett Ninness |
Scheme | Travel Grant |
Role | Lead |
Funding Start | 1994 |
Funding Finish | 1994 |
GNo | G0175109 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
19931 grants / $2,300
'Annual IEEE Conf. on Decision & Control', San Antonio, Texas, 15 - 17 Dec 1993$2,300
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Professor Brett Ninness |
Scheme | Travel Grant |
Role | Lead |
Funding Start | 1993 |
Funding Finish | 1993 |
GNo | G0174433 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
19921 grants / $10,000
Research On Industrial Control Projects$10,000
Funding body: Department of Industry, Science and Resources
Funding body | Department of Industry, Science and Resources |
---|---|
Project Team | Emeritus Laureate Professor Graham Goodwin, Professor Brett Ninness |
Scheme | DIST Advanced Manufacturing Technology (Defunct) |
Role | Investigator |
Funding Start | 1992 |
Funding Finish | 1992 |
GNo | G0173426 |
Type Of Funding | Aust Competitive - Commonwealth |
Category | 1CS |
UON | Y |
Research Supervision
Number of supervisions
Past Supervision
Year | Level of Study | Research Title | Program | Supervisor Type |
---|---|---|---|---|
2016 | Masters | Computational Solutions for Bayesian Inference in Dynamical Systems | M Philosophy(Elec Engineering), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2014 | PhD | Soft Detection of Spatially Diverse Wireless Communications via Stochastic Sampling | PhD (Computer Engineering), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2013 | PhD | Algorithms and Hardware Implementation of a Processor for Low Complexity and High Performance Multi-Antenna Receivers | PhD (Computer Engineering), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2013 | PhD | Computational Bayesian Methods for Communications and Control | PhD (Electrical Engineering), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2010 | PhD | Vibration and Position Control of Piezoelectric Tube Scanners for Fast Atomic Force Microscopy | PhD (Electrical Engineering), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2009 | Masters | A Reconfigurable Prototyping System for Multiple-Input Multiple-Output Communications | M Engineering (Elec & Comp)[R], College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2009 | Masters | Design of Low-Density Parity-Check Codes for Multiple-Input Multiple-Output Wireless Systems | M Engineering (Elec & Comp)[R], College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2007 | PhD | Algorithms and Application Specific Integrated Circuits for Combinatorial Optimisation in Wireless Communications | PhD (Computer Engineering), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2003 | PhD | Maximum Likelihood Estimation of Multivariable Dynamic Systems via the EM algorithm | PhD (Electrical Engineering), College of Engineering, Science and Environment, The University of Newcastle | Sole Supervisor |
2002 | Masters | Modern CDMA Wireless Communication Systems | M Engineering (Elec & Comp)[R], College of Engineering, Science and Environment, The University of Newcastle | Sole Supervisor |
News
News • 29 Nov 2019
Showcasing the latest engineering solutions
From a shark-proof wetsuit to an interactive boxing robot, a public exhibition taking place in Newcastle over the next nine days will showcase cutting-edge engineering and computing innovations from the University of Newcastle.
News • 5 Jan 2017
UON engineer recognised for global impact on humanity
A University of Newcastle (UON) academic has received global recognition for his work contributing to the advancement and application of engineering, resulting in a significant impact on society.
Professor Brett Ninness
Position
Professor
School of Engineering
College of Engineering, Science and Environment
Focus area
Electrical and Computer Engineering
Contact Details
brett.ninness@newcastle.edu.au | |
Phone | (02) 4921 7071 |
Mobile | 0438614163 |
Fax | (02) 4921 6993 |
Office
Room | ES317 |
---|---|
Building | Engineering A Building. |
Location | Callaghan University Drive Callaghan, NSW 2308 Australia |