System Identification with Quantized Observations

  • Le Yi Wang
  • G. George Yin
  • Ji-Feng Zhang
  • Yanlong Zhao
Part of the Systems & Control: Foundations & Applications book series (SCFA)

Table of contents

  1. Front Matter
    Pages i-xviii
  2. Overview

    1. Front Matter
      Pages 1-1
    2. Le Yi Wang, G. George Yin, Ji-Feng Zhang, Yanlong Zhao
      Pages 3-11
    3. Le Yi Wang, G. George Yin, Ji-Feng Zhang, Yanlong Zhao
      Pages 13-22
  3. Stochastic Methods for Linear Systems

    1. Front Matter
      Pages 23-23
    2. Le Yi Wang, G. George Yin, Ji-Feng Zhang, Yanlong Zhao
      Pages 25-47
    3. Le Yi Wang, G. George Yin, Ji-Feng Zhang, Yanlong Zhao
      Pages 49-57
    4. Le Yi Wang, G. George Yin, Ji-Feng Zhang, Yanlong Zhao
      Pages 59-66
    5. Le Yi Wang, G. George Yin, Ji-Feng Zhang, Yanlong Zhao
      Pages 67-79
    6. Le Yi Wang, G. George Yin, Ji-Feng Zhang, Yanlong Zhao
      Pages 81-93
    7. Le Yi Wang, G. George Yin, Ji-Feng Zhang, Yanlong Zhao
      Pages 95-116
  4. Deterministic Methods for Linear Systems

    1. Front Matter
      Pages 117-117
    2. Le Yi Wang, G. George Yin, Ji-Feng Zhang, Yanlong Zhao
      Pages 119-147
    3. Le Yi Wang, G. George Yin, Ji-Feng Zhang, Yanlong Zhao
      Pages 149-169
  5. Identification of Nonlinear and Switching Systems

    1. Front Matter
      Pages 171-171
    2. Le Yi Wang, G. George Yin, Ji-Feng Zhang, Yanlong Zhao
      Pages 173-195
    3. Le Yi Wang, G. George Yin, Ji-Feng Zhang, Yanlong Zhao
      Pages 197-223
    4. Le Yi Wang, G. George Yin, Ji-Feng Zhang, Yanlong Zhao
      Pages 225-252
  6. Complexity Analysis

    1. Front Matter
      Pages 253-253
    2. Le Yi Wang, G. George Yin, Ji-Feng Zhang, Yanlong Zhao
      Pages 255-273

About this book

Introduction

This book presents recently developed methodologies that utilize quantized information in system identification and explores their potential in extending control capabilities for systems with limited sensor information or networked systems. The results of these methodologies can be applied to signal processing and control design of communication and computer networks, sensor networks, mobile agents, coordinated data fusion, remote sensing, telemedicine, and other fields in which noise-corrupted quantized data need to be processed.

Providing a comprehensive coverage of quantized identification, the book treats linear and nonlinear systems, as well as time-invariant and time-varying systems. The authors examine independent and dependent noises, stochastic- and deterministic-bounded noises, and also noises with unknown distribution functions. The key methodologies combine empirical measures and information-theoretic approaches to derive identification algorithms, provide convergence and convergence speed, establish efficiency of estimation, and explore input design, threshold selection and adaptation, and complexity analysis.

System Identification with Quantized Observations is an excellent resource for graduate students, systems theorists, control engineers, applied mathematicians, as well as practitioners who use identification algorithms in their work. Selected material from the book may be used in graduate-level courses on system identification.

Keywords

Analysis Markov Signal algorithm algorithms communication identification nonlinear system system system identification

Authors and affiliations

  • Le Yi Wang
    • 1
  • G. George Yin
    • 2
  • Ji-Feng Zhang
    • 3
  • Yanlong Zhao
    • 4
  1. 1.Department of Electrical &, Computer EngineeringWayne State UniversityDetroitUSA
  2. 2.Department of MathematicsWayne State UniversityDetroitUSA
  3. 3.Academy of Mathematics & Systems Sci., Inst. Systems ScienceChinese Academy of SciencesBeijingChina, People's Republic
  4. 4.Academy of Mathematics & Systems Sci., Inst. Systems ScienceChinese Academy of SciencesBeijingChina, People's Republic

Bibliographic information

  • DOI https://doi.org/10.1007/978-0-8176-4956-2
  • Copyright Information Springer Science+Business Media, LLC 2010
  • Publisher Name Birkhäuser Boston
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-0-8176-4955-5
  • Online ISBN 978-0-8176-4956-2