Overview
- 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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Keywords
Table of contents (15 chapters)
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Overview
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Stochastic Methods for Linear Systems
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Deterministic Methods for Linear Systems
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Identification of Nonlinear and Switching Systems
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Complexity Analysis
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
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