Blind signal processing

Blind signal processing: theory and practice

by Shi, Xizhi

Type Book
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"Blind Signal Processing: Theory and Practice" not only introduces related fundamental mathematics, but also reflects the numerous advances in the field, such as probability density estimation-based processing algorithms, underdetermined models, complex value methods, uncertainty of order in the separation of convolutive mixtures in frequency domains, and feature extraction using Independent Component Analysis (ICA). At the end of the book, results from a study conducted at Shanghai Jiao Tong U…

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Title Statements

  • Full title :Blind signal processing : theory and practice / Xizhi Shi.

Summary

"Blind Signal Processing: Theory and Practice" not only introduces related fundamental mathematics, but also reflects the numerous advances in the field, such as probability density estimation-based processing algorithms, underdetermined models, complex value methods, uncertainty of order in the separation of convolutive mixtures in frequency domains, and feature extraction using Independent Component Analysis (ICA). At the end of the book, results from a study conducted at Shanghai Jiao Tong University in the areas of speech signal processing, underwater signals, image feature extraction, data compression, and the like are discussed. This book will be of particular interest to advanced undergraduate students, graduate students, university instructors and research scientists in related disciplines. Xizhi Shi is a Professor at Shanghai Jiao Tong University

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Edition Statements

  • Publication Date:©2011.

Publication Statements

The Physical Object

  • Description:1 online resource (xiv, 368 pages)

Edition Identifiers

  • ISBN:9783642113475, 3642113478
  • oclc:ocn771921036
  • LC Classification:TK5102.9
  • Dewey Decimal:621.382/2

Table of Contents

Chapter 1. Introduction -- Chapter 2. Mathematical Description of Blind Signal Processing -- Chapter 3. Independent Component Analysis (ICA) -- Chapter 4. Non-Linear Principal Component Analysis (PCA) and Feature Extraction -- Chapter 5. Non-Linear ICA -- Chapter 6. Convolutive Mixture and Blind Deconvolution -- Chapter 7. Probability Density Estimation Based Blind Processing Algorithm -- Chapter 8. Joint Approximate Diagonalization method -- Features in Frequency Domain and Time Domain -- Chapter 9. Extension of Blind Signal Processing -- Chapter 10. Data Analysis and Application Study.

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