System Parameter Identification

Information Criteria and Algorithms
Erscheinungsjahr 2013
ISBN: 978-0-12-404574-3
Verlag: Elsevier Science Publishing Co Inc

Buch, Englisch, 266 Seiten, Format (B × H): 156 mm x 236 mm, Gewicht: 523 g

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. The authors' research provides a base for the book, but it incorporates the results from the latest international research publications.

Zielgruppe

<p>Engineers, scientists and graduate students interested in information theory, signal processing, system identification and adaptive system training.</p>

Autoren/Hrsg.

Chen, Badong

Zhu, Yu

Hu, Jinchun

Principe, Jose C.

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Informationstheorie, Kodierungstheorie
• Mathematik | Informatik Mathematik Mathematik Interdisziplinär Systemtheorie
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Informationstheorie, Kodierungstheorie
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Regelungstechnik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Signalverarbeitung
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Kybernetik, Systemtheorie, Komplexe Systeme

Inhaltsverzeichnis

1.Introduction2.Information Measures3.Information Theoretic Estimation4.System Identification Under Minimum Error Entropy Criteria5.System Identification Under Information Divergence Criteria6.System Identification Based on Mutual Information Criteria

Über Autor(innen)

Chen, Badong
Badong Chen received the B.S. and M.S. degrees in control theory and engineering from Chongqing University, in 1997 and 2003, respectively, and the Ph.D. degree in computer science and technology from Tsinghua University in 2008. He was a Post-Doctoral Researcher with Tsinghua University from 2008 to 2010, and a Post-Doctoral Associate at the University of Florida Computational NeuroEngineering Laboratory (CNEL) during the period October, 2010 to September, 2012. He is currently a professor at the Institute of Artificial Intelligence and Robotics (IAIR), Xi'an Jiaotong University. His research interests are in system identification and control, information theory, machine learning, and their applications in cognition and neuroscience.

Principe, Jose C.
Jose C. Principe is a Distinguished Professor of Electrical and Computer Engineering and Biomedical Engineering at the University of Florida where he teaches advanced signal processing, machine learning and artificial neural networks (ANNs) modeling. He is BellSouth Professor and the Founding Director of the University of Florida Computational NeuroEngineering Laboratory (CNEL). His primary research interests are in advanced signal processing with information theoretic criteria (entropy and mutual information) and adaptive models in reproducing kernel Hilbert spaces (RKHS), and the application of these advanced algorithms to Brain Machine Interfaces (BMI). Dr. Principe is a Fellow of the IEEE, ABME, and AIBME. He is the past Editor in Chief of the IEEE Transactions on Biomedical Engineering, past Chair of the Technical Committee on Neural Networks of the IEEE Signal Processing Society, and Past-President of the International Neural Network Society. He received the IEEE EMBS Career Award, and the IEEE Neural Network Pioneer Award. He has more than 600 publications and 30 patents (awarded or filed).

Hu, Jinchun
Jinchun Hu,associate professor, born in 1972, graduated from Nanjing University of Science & Technology. He received the B.Eng and Ph.D. degrees in control science and engineering in 1994 and 1998, respectively. Now he works at the Department of Mechanical Engineering, Tsinghua University. His current research interests include modern control theory and control systems, ultra-precision measurement principles and methods, micro/nano motion control system analysis and realization, special driver technology and device for precision motion systems, and super-precision measurement & control.

Zhu, Yu
Yu Zhu received the B.S. degree in radio electronics in 1983 from Beijing Normal University, and the M.S. degree in computer applications in 1993, and the Ph.D. degree in mechanical design and theory in 2001, both from China University of Mining and Technology. He is currently a professor with the Department of Mechanical Engineering, Tsinghua University. His research field mainly covers IC manufacturing equipment development strategy, ultra-precision air/maglev stage machinery design theory and technology, ultra-precision measurement theory and technology, and precision motion control theory and technology. Prof. Zhu has more than 140 research papers and 100 (48 awarded) invention patents.