World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
37
Citations
6469
World Ranking
8317
National Ranking
413

Research.com Recognitions

  • 2017 - IEEE Fellow For contributions to computational methods in system identification

Overview

Brett Ninness is affiliated with the University of Newcastle Australia and contributes primarily to the fields of Engineering and Computer Science. Their research work encompasses subfields such as Control and Systems Engineering, Artificial Intelligence, Electrical and Electronic Engineering, Statistics and Probability, and Biomedical Engineering.

The scientist's work addresses main topics including Control Systems and Identification, Target Tracking and Data Fusion in Sensor Networks, Fault Detection and Control Systems, Gaussian Processes and Bayesian Inference, Advanced Control Systems Optimization, Bayesian Modeling and Causal Inference, and Markov Chains and Monte Carlo Methods.

Recent publications include:

  • Parameter estimation for Jump Markov Linear Systems, 2021, Automatica
  • A new smoothing algorithm for jump Markov linear systems, 2022, Automatica
  • Variational system identification for nonlinear state-space models, 2022, Automatica
  • Design of fractional-order hammerstein control auto-regressive model for heat exchanger system identification: Treatise on fuzzy-evolutionary computing, 2024, Chaos Solitons & Fractals
  • Large-Amplitude Dithering Mitigates Glitches in Digital-to-Analogue Converters, 2020, IEEE Transactions on Signal Processing

Frequent co-authors associated with Brett Ninness include:

  • Adrian Wills
  • Christopher Renton
  • Mark P. Balenzuela
  • Kalle Åström
  • Robert R. Bitmead

Journals and conferences where the scientist has often published are:

  • arXiv (Cornell University)
  • International Journal of Adaptive Control and Signal Processing
  • Automatica
  • IFAC-PapersOnLine
  • Chaos Solitons & Fractals

Brett Ninness was recognized as an IEEE Fellow in 2017 for contributions to computational methods in system identification.

Best Publications

  • System identification of nonlinear state-space models

    Thomas B. Schön;Adrian Wills;Brett Ninness

  • A unifying construction of orthonormal bases for system identification

    B. Ninness;F. Gustafsson

  • Quantifying the error in estimated transfer functions with application to model order selection

    G.C. Goodwin;M. Gevers;B. Ninness

  • Identification of Hammerstein-Wiener models

    Adrian Wills;Thomas B. SchöN;Lennart Ljung;Brett Ninness

  • Modelling and Identification with Rational Orthogonal Basis Functions

    Paul Van den Hof;Bo Wahlberg;Peter Heuberger;Brett Ninness

  • Robust maximum-likelihood estimation of multivariable dynamic systems

    Stuart Gibson;Brett Ninness

  • Estimation of model quality

    Brett Ninness;Graham C. Goodwin

  • The fundamental role of general orthonormal bases in system identification

    B. Ninness;H. Hjalmarsson;F. Gustafsson

  • Model Predictive Control Applied to Constraint Handling in Active Noise and Vibration Control

    A.G. Wills;D. Bates;A.J. Fleming;B. Ninness

  • Orthonormal basis functions for modelling continuous-time systems

    Hüseyin Akçay;Brett Ninness

  • Rational basis functions for robust identification from frequency and time domain measurements

    H. Akcay;B. Ninness

  • On Gradient-Based Search for Multivariable System Estimates

    A. Wills;B. Ninness

  • Quantification of Uncertainty in Estimation

    Graham C. Goodwin;Brett Ninness;Mario E. Salgado

  • Sampling zeros and the Euler-Frobenius polynomials

    S.R. Weller;W. Moran;B. Ninness;A.D. Pollington

  • Bayesian system identification via Markov chain Monte Carlo techniques

    Brett Ninness;Soren Henriksen

  • Maximum-likelihood parameter estimation of bilinear systems

    S. Gibson;A. Wills;B. Ninness

  • Estimation of 1/f noise

    B. Ninness

  • Fast Linear Model Predictive Control Via Custom Integrated Circuit Architecture

    A. G. Wills;G. Knagge;B. Ninness

  • Variance error quantifications that are exact for finite-model order

    B. Ninness;H. Hjalmarsson

  • Generalized Fourier and Toeplitz Results for Rational Orthonormal Bases

    Brett Ninness;Hakan Hjalmarsson;Fredrik Gustafsson

  • Sampling zeros and the Euler-Frobenius polynomials

    S.R. Weller;W. Moran;B. Ninnes;A.D. Pollington

Frequent Co-Authors

Håkan Hjalmarsson
Håkan Hjalmarsson Royal Institute of Technology
Graham C. Goodwin
Graham C. Goodwin University of Newcastle Australia
Thomas B. Schön
Thomas B. Schön Uppsala University
Fredrik Gustafsson
Fredrik Gustafsson Linköping University
Minyue Fu
Minyue Fu Southern University of Science and Technology
Andrew J. Fleming
Andrew J. Fleming University of Newcastle Australia
Michel Gevers
Michel Gevers Université Catholique de Louvain
Syed Islam
Syed Islam Federation University Australia
Daniel E. Quevedo
Daniel E. Quevedo University of Sydney
Lennart Ljung
Lennart Ljung Linköping University

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