J
John B. Moore
Researcher at Australian National University
Publications - 352
Citations - 19139
John B. Moore is an academic researcher from Australian National University. The author has contributed to research in topics: Adaptive control & Linear-quadratic-Gaussian control. The author has an hindex of 50, co-authored 352 publications receiving 18573 citations. Previous affiliations of John B. Moore include Akita University & University of Hong Kong.
Papers
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Brief paper: On strong consistency of least squares identification algorithms
TL;DR: Almost sure convergence results are derived for least squares identification algorithms for asymptotically stable signal models and possibly nonstationary processes and the Toeplitz lemma.
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Dikin-Type Algorithms for Dextrous Grasping Force Optimization
TL;DR: In this paper, two versions of strictly convex cost functions, one of them self-concordant, are considered and it is shown that the proposed algo rithms guarantee convergence to the unique solution of the semidefinite programming problem associated with dextrous grasping force optimization.
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Spectral factorization of time-varying covariance functions
TL;DR: It is shown that a symmetric state covariance matrix provides the key link between the state-space equations of a system and the system output covariance matrices.
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Convergence of adaptive minimum variance algorithms via weighting coefficient selection
R. Kumar,John B. Moore +1 more
TL;DR: Weighted least squares and related stochastic approximation algorithms are studied for parameter estimation, adaptive state estimation and adaptive N -step-ahead prediction, in both white and colored noise environments.
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On the Youla-Kucera parametrization for nonlinear systems
A.D.B. Paice,John B. Moore +1 more
TL;DR: In this paper, a nonlinear generalization of the Youla-Kucera parametrization for nonlinear systems is presented, and the equivalence of the class of all (bounded-input) stabilizing nonlinear pre- and feedback-compensators to a class of possibly unstable feedback controllers is shown.