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Blind Source Separation

Dependent Component Analysis

  • Book
  • © 2015

Overview

Authors:
  1. Yong Xiang

    1. School of Information Technology, Deakin University, Melbourne, Australia

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  2. Dezhong Peng

    1. Computer Science, Sichuan University, Chengdu, China

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    You can also search for this author in PubMed   Google Scholar

  3. Zuyuan Yang

    1. Faculty of Automation, Guangdong University of Technology, Guangzhou, China

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    You can also search for this author in PubMed   Google Scholar

  • First book addressing blind separation of mutually correlated sources
  • Presents novel blind source seperation algorithms that are applicable world applications
  • Written by leading experts in the field
  • Includes supplementary material: sn.pub/extras

Part of the book series: SpringerBriefs in Electrical and Computer Engineering (BRIEFSELECTRIC)

Part of the book sub series: SpringerBriefs in Signal Processing (BRIEFSSIGNAL)

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Table of contents (5 chapters)

  1. Front Matter

    Pages i-xii
    Download chapter PDF

  2. Introduction

    • Yong Xiang, Dezhong Peng, Zuyuan Yang
    Pages 1-17

  3. Dependent Component Analysis Exploiting Nonnegativity and/or Time-Domain Sparsity

    • Yong Xiang, Dezhong Peng, Zuyuan Yang
    Pages 19-47

  4. Dependent Component Analysis Using Time-Frequency Analysis

    • Yong Xiang, Dezhong Peng, Zuyuan Yang
    Pages 49-71

  5. Dependent Component Analysis Using Precoding

    • Yong Xiang, Dezhong Peng, Zuyuan Yang
    Pages 73-90

  6. Future Work

    • Yong Xiang, Dezhong Peng, Zuyuan Yang
    Pages 91-94
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Keywords

About this book

This book provides readers a complete and self-contained set of knowledge about dependent source separation, including the latest development in this field. The book gives an overview on blind source separation where three promising blind separation techniques that can tackle mutually correlated sources are presented. The book further focuses on the non-negativity based methods, the time-frequency analysis based methods, and the pre-coding based methods, respectively.

Authors and Affiliations

  • School of Information Technology, Deakin University, Melbourne, Australia

    Yong Xiang

  • Computer Science, Sichuan University, Chengdu, China

    Dezhong Peng

  • Faculty of Automation, Guangdong University of Technology, Guangzhou, China

    Zuyuan Yang

About the authors

Yong Xiang received the B.E. and M.E. degrees from the University of Electronic Science and Technology of China, Chengdu, China, in 1983 and 1989, respectively. In 2003, he received the Ph.D. degree from The University of Melbourne, Melbourne, Australia. He was with the Southwest Institute of Electronic Equipment of China, Chengdu, from 1983 to 1986. In 1989, he joined the University of Electronic Science and Technology of China, where he was a Lecturer from 1989 to 1992 and an Associate Professor from 1992 to 1997. He was a Senior Communications Engineer with Bandspeed Inc., Melbourne, Australia, from 2000 to 2002. He is currently an Associate Professor with the School of Information Technology at Deakin University, Australia. His research interests include blind signal/system estimation, communication signal processing, information and network security, speech and image processing, and pattern recognition.

Dezhong Peng received the B.S. degree in applied mathematics, the M.S. and Ph.D. degrees in computer software and theory from the University of Electronic Science and Technology of China, Chengdu, China, in 1998, 2001 and 2006, respectively. He was a Postdoctoral Research Fellow at the School of Engineering, Deakin University, Australia from 2007 to 2009. Currently, he is a Professor at the Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, China. His current research interests include blind signal processing and neural networks.

Zuyuan Yang received the B.E. degree from Hunan University of Science and Technology, Xiangtan, China, and the Ph.D. degree from South China University of Technology, Guangzhou, China, in 2003 and 2010, respectively. He was a recipient of the Excellent Ph.D. Thesis Award of Guangdong Province in 2010. Dr Yang is currently a Researcher with the Faculty of Automation, Guangdong University of Technology, Guangzhou. His current research interests include blind source separation, compressed sensing, nonnegative matrix factorization, and image processing.

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