John Barratt Moore 1941–2013
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TLDR
Moore as mentioned in this paper was an electrical engineer who spent most of his distinguished career at the University of Newcastle and the Australian National University following industrial experience and graduate education in Silicon Valley, California, achieving all honours at a comparatively early age, and was recognized principally for his contributions to the field of control systems.Abstract:
John Moore was born in Lungling, China on 3 April 1941 and died in Canberra on 19 January 2013. He was an electrical engineer who spent most of his distinguished career at the University of Newcastle and the Australian National University following industrial experience and graduate education in Silicon Valley, California. He was a Fellow of the Institute of Electrical and Electronic Engineers, the Australian Academy of Science and the Australian Academy of Technological Sciences and Engineering, achieving all honours at a comparatively early age, and was recognized principally for his contributions to the field of control systems.read more
Citations
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Proceedings ArticleDOI
On adaptive estimation and pole assignment of overparametrized systems
TL;DR: The methods proposed in the paper are relatively simple compared to on-line order determination, being based on introducing suitable excitation in the "regression" vectors of the parameter estimation algorithms to ensure parameter convergence.
Factorizations that relax the positive real condition in continuous-time ELS schemes
TL;DR: In this article, Extended Least Squares (ELS) schemes for ARMAX model identification of continuous-time systems were proposed, which have a relaxed Strictly Positive Real (SPR) condition for global convergence.
References
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Journal Article
Optimal Filtering
TL;DR: This book helps to fill the void in the market and does that in a superb manner by covering the standard topics such as Kalman filtering, innovations processes, smoothing, and adaptive and nonlinear estimation.
Book
Optimal Control: Linear Quadratic Methods
TL;DR: In this article, an augmented edition of a respected text teaches the reader how to use linear quadratic Gaussian methods effectively for the design of control systems, with step-by-step explanations that show clearly how to make practical use of the material.
Book
Hidden Markov Models: Estimation and Control
TL;DR: This paper presents a meta-modelling procedure called Markov Model Processing that automates the very labor-intensive and therefore time-heavy and therefore expensive process of HMMEstimation.
Book
Optimization and Dynamical Systems
Uwe Helmke,John B. Moore +1 more
TL;DR: Details of Matrix Eigenvalue Methods, including Double Bracket Isospectral Flows, and Singular Value Decomposition are revealed.