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System parameter identification : information criteria and algorithms / Badong Chen, Institute of Artificial Intelligence and Robotics (IAIR), Xi'an Jiaotong University, Xi'an, China, Yu Zhu, Department of Mechanical Engineering, Tsinghua University, Beijing, China, Jinchun Hu, Department of Mechanical Engineering, Tsinghua University, Beijing, China, Jose C. Principe, Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA.

By: Chen, Badong [author.]
Contributor(s): Zhu, Yu [author.] | Hu, Jinchun [author.] | Príncipe, J. C. (José C.) [author.]
Material type: TextTextPublisher: London, UK ; Waltham, MA, USA : Elsevier, 2013Edition: First editionDescription: xv, 249 pages : illustrations ; 24 cmContent type: text Media type: unmediated Carrier type: volumeISBN: 9780124045743; 012404574XSubject(s): System identification | Computer algorithms | Computer algorithms | System identificationDDC classification: 629.8312 LOC classification: QA402 | .C4385 2013Online resources: Publisher description 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.--
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Item type Current location Call number Status Date due Barcode
Books Books Centeral Library
Second Floor - Engineering & Architecture
629.8312 C.B.S 2013 (Browse shelf) Available 21850
Books Books Centeral Library
Second Floor - Engineering & Architecture
629.8312 C.B.S 2013 (Browse shelf) Available 21851

Includes bibliographical references (pages 239-249) and index.

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.--

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