Authors:
- First monograph dedicated to quantized identification in systems
- Applications to communication and computer networks, signal processing, sensor networks, mobile agents, data fusion, remote sensing, telemedicine
- Selected material from the book may be used in graduate-level courses on system identification
- Includes supplementary material: sn.pub/extras
Part of the book series: Systems & Control: Foundations & Applications (SCFA)
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Table of contents (15 chapters)
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Front Matter
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Overview
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Front Matter
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Stochastic Methods for Linear Systems
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Front Matter
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Deterministic Methods for Linear Systems
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Front Matter
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Identification of Nonlinear and Switching Systems
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Front Matter
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Complexity Analysis
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Front Matter
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About this book
Reviews
From the reviews:
“The central idea in this book is to provide a comprehensive treatment of both theory and algorithms needed for parameter identification of systems with quantized observations. … the book conveys a clear and very complete overview of recent exciting developments in the area of identification with quantized observations. It is meant as a ‘state-of-the-art’ book … . All this makes the book an extremely valuable resource for researchers and engineers interested in modern system identification.” (Dariusz Uciński, Mathematical Reviews, Issue 2011 i)Authors and Affiliations
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Department of Electrical &, Computer Engineering, Wayne State University, Detroit, USA
Le Yi Wang
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Department of Mathematics, Wayne State University, Detroit, USA
G. George Yin
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Academy of Mathematics & Systems Sci., Inst. Systems Science, Chinese Academy of Sciences, Beijing, China, People's Republic
Ji-Feng Zhang, Yanlong Zhao
Bibliographic Information
Book Title: System Identification with Quantized Observations
Authors: Le Yi Wang, G. George Yin, Ji-Feng Zhang, Yanlong Zhao
Series Title: Systems & Control: Foundations & Applications
DOI: https://doi.org/10.1007/978-0-8176-4956-2
Publisher: Birkhäuser Boston, MA
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Science+Business Media, LLC 2010
Hardcover ISBN: 978-0-8176-4955-5Published: 25 May 2010
eBook ISBN: 978-0-8176-4956-2Published: 18 May 2010
Series ISSN: 2324-9749
Series E-ISSN: 2324-9757
Edition Number: 1
Number of Pages: XVIII, 317
Number of Illustrations: 42 b/w illustrations
Topics: Systems Theory, Control, Mathematical Modeling and Industrial Mathematics, Control and Systems Theory, Algorithms, Communications Engineering, Networks, Probability Theory and Stochastic Processes