System parameter identification : information criteria and algorithms /

Recently, criterion functions based on information theoretic measures (entropy, mutual information, information divergence) have attracted attention and become an emerging area of study in signal processing and system identification domain. This book presents a systematic framework for system identi...

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Bibliographic Details
Main Authors: Chen, Badong
Corporate Authors: Elsevier Science & Technology.
Group Author: Zhu, Yu; Hu, Jinchun; Príncipe, J. C. (José C.)
Published: Elsevier,
Publisher Address: London, UK :
Publication Dates: 2013.
Literature type: eBook
Language: English
Edition: First edition.
Series: Elsevier insights
Subjects:
Online Access: http://www.sciencedirect.com/science/book/9780124045743
Summary: Recently, criterion functions based on information theoretic measures (entropy, mutual information, information divergence) have attracted attention and become an emerging area of study in signal processing and system identification domain. This book presents a systematic framework for system identification and information processing, investigating system identification from an information theory point of view. The book is divided into six chapters, which cover the information needed to understand the theory and application of system parameter identification.
Carrier Form: 1 online resource (xv, 249 pages) : illustrations.
Bibliography: Includes bibliographical references.
ISBN: 9780124045958
0124045952
Index Number: QA3
CLC: O235
Contents: 1. Introduction -- 2. Information measures -- 3. Information theoretic parameter estimation -- 4. System identification under minimum error entropy criteria -- 5. System identification under information divergence criteria -- 6. System identification based on mutual information criteria.