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Systems & Control: Foundations & Applications

System Identification with Quantized Observations

Authors: Wang, L.Y., Yin, G., Zhang, J.-F., Zhao, Y.

  • 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
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Buy this book

eBook $149.00
price for USA (gross)
  • ISBN 978-0-8176-4956-2
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $199.00
price for USA
  • ISBN 978-0-8176-4955-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

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.

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)

Table of contents (15 chapters)

  • Introduction

    Wang, Le Yi (et al.)

    Pages 3-11

  • System Settings

    Wang, Le Yi (et al.)

    Pages 13-22

  • Empirical-Measure-Based Identification: Binary-Valued Observations

    Wang, Le Yi (et al.)

    Pages 25-47

  • Estimation Error Bounds: Including Unmodeled Dynamics

    Wang, Le Yi (et al.)

    Pages 49-57

  • Rational Systems

    Wang, Le Yi (et al.)

    Pages 59-66

Buy this book

eBook $149.00
price for USA (gross)
  • ISBN 978-0-8176-4956-2
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $199.00
price for USA
  • ISBN 978-0-8176-4955-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
System Identification with Quantized Observations
Authors
Series Title
Systems & Control: Foundations & Applications
Copyright
2010
Publisher
Birkhäuser Basel
Copyright Holder
Springer Science+Business Media, LLC
eBook ISBN
978-0-8176-4956-2
DOI
10.1007/978-0-8176-4956-2
Hardcover ISBN
978-0-8176-4955-5
Series ISSN
2324-9749
Edition Number
1
Number of Pages
XVIII, 317
Number of Illustrations and Tables
42 b/w illustrations
Topics