SpringerBriefs in Mathematics

System Identification Using Regular and Quantized Observations

Applications of Large Deviations Principles

Authors: He, Qi, Wang, Le Yi, Yin, George G.

  • ​ Presents characterizations of identification errors under a probabilistic framework when output sensors are binary, quantized, or regular
  • First book devoted to large deviations to system identification
  • Application oriented
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eBook $34.99
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  • ISBN 978-1-4614-6292-7
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Softcover $49.95
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About this book

​This brief presents characterizations of identification errors under a probabilistic framework when output sensors are binary, quantized, or regular.  By considering both space complexity in terms of signal quantization and time complexity with respect to data window sizes, this study provides a new perspective to understand the fundamental relationship between probabilistic errors and resources, which may represent data sizes in computer usage, computational complexity in algorithms, sample sizes in statistical analysis and channel bandwidths in communications.

Table of contents (9 chapters)

  • Introduction and Overview

    He, Qi (et al.)

    Pages 1-7

  • System Identification: Formulation

    He, Qi (et al.)

    Pages 9-10

  • Large Deviations: An Introduction

    He, Qi (et al.)

    Pages 11-15

  • LDP of System Identification under Independent and Identically Distributed Observation Noises

    He, Qi (et al.)

    Pages 17-35

  • LDP of System Identification under Mixing Observation Noises

    He, Qi (et al.)

    Pages 37-42

Buy this book

eBook $34.99
price for USA (gross)
  • ISBN 978-1-4614-6292-7
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $49.95
price for USA
  • ISBN 978-1-4614-6291-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the ebook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
System Identification Using Regular and Quantized Observations
Book Subtitle
Applications of Large Deviations Principles
Authors
Series Title
SpringerBriefs in Mathematics
Copyright
2013
Publisher
Springer-Verlag New York
Copyright Holder
Qi He, Le Yi Wang, and G. George Yin
eBook ISBN
978-1-4614-6292-7
DOI
10.1007/978-1-4614-6292-7
Softcover ISBN
978-1-4614-6291-0
Series ISSN
2191-8198
Edition Number
1
Number of Pages
XII, 95
Number of Illustrations and Tables
1 b/w illustrations, 16 illustrations in colour
Topics