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Brian D. O. Anderson
Researcher at Australian National University
Publications - 1120
Citations - 50069
Brian D. O. Anderson is an academic researcher from Australian National University. The author has contributed to research in topics: Linear system & Control theory. The author has an hindex of 96, co-authored 1107 publications receiving 47104 citations. Previous affiliations of Brian D. O. Anderson include University of Newcastle & Eindhoven University of Technology.
Papers
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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.
Journal ArticleDOI
Wireless sensor network localization techniques
TL;DR: An overview of the measurement techniques in sensor network localization and the one-hop localization algorithms based on these measurements are provided and a detailed investigation on multi-hop connectivity-based and distance-based localization algorithms are presented.
Journal ArticleDOI
Digital control of dynamic systems
TL;DR: Digital Control Of Dynamic Systems This well-respected, market-leading text discusses the use of digital computers in the real-time control of dynamic systems with an emphasis on the design of digital controls that achieve good dynamic response and small errors while using signals that are sampled in time and quantized in amplitude.
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A Theory of Network Localization
James Aspnes,Tolga Eren,David K. Goldenberg,A.S. Morse,Walter Whiteley,Yang Yang,Brian D. O. Anderson,Peter N. Belhumeur +7 more
TL;DR: This paper constructs grounded graphs to model network localization and applies graph rigidity theory to test the conditions for unique localizability and to construct uniquely localizable networks, and further study the computational complexity of network localization.