Open access peer-reviewed Edited Volume

Independent Component Analysis for Audio and Biosignal Applications

Edited by Ganesh R. Naik

RMIT University, Australia

Independent Component Analysis (ICA) is a signal-processing method to extract independent sources given only observed data that are mixtures of the unknown sources. Recently, Blind Source Separation (BSS) by ICA has received considerable attention because of its potential signal-processing applications such as speech enhancement systems, image processing, telecommunications, medical signal processing and several data mining issues. This book brings the state-of-the-art of some of the most important current research of ICA related to Audio and Biomedical signal processing applications. The book is partly a textbook and partly a monograph. It is a textbook because it gives a detailed introduction to ICA applications. It is simultaneously a monograph because it presents several new results, concepts and further developments, which are brought together and published in the book.

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Independent Component Analysis for Audio and Biosignal ApplicationsEdited by Ganesh R. Naik

Published: October 10th 2012

DOI: 10.5772/3084

ISBN: 978-953-51-0782-8

eBook (PDF) ISBN: 978-953-51-6245-2

Copyright year: 2012

Books open for chapter submissions

30361 Total Chapter Downloads

10 Crossref Citations

14 Web of Science Citations

13 Dimensions Citations


Open access peer-reviewed

1. Introduction: Independent Component Analysis

By Ganesh R. Naik


Open access peer-reviewed

2. On Temporomandibular Joint Sound Signal Analysis Using ICA

By Feng Jin and Farook Sattar


Open access peer-reviewed

3. Blind Source Separation for Speech Application Under Real Acoustic Environment

By Hiroshi Saruwatari and Yu Takahashi


Open access peer-reviewed

4. Monaural Audio Separation Using Spectral Template and Isolated Note Information

By Anil Lal and Wenwu Wang


Open access peer-reviewed

5. Non-Negative Matrix Factorization with Sparsity Learning for Single Channel Audio Source Separation

By Bin Gao and W.L. Woo


Open access peer-reviewed

6. Unsupervised and Neural Hybrid Techniques for Audio Signal Classification

By Andrés Ortiz, Lorenzo J. Tardón, Ana M. Barbancho and Isabel Barbancho


Open access peer-reviewed

7. Convolutive ICA for Audio Signals

By Masoud Geravanchizadeh and Masoumeh Hesam


Open access peer-reviewed

8. Nonlinear Independent Component Analysis for EEG-Based Brain-Computer Interface Systems

By Farid Oveisi, Shahrzad Oveisi, Abbas Efranian and Ioannis Patras


Open access peer-reviewed

9. Associative Memory Model Based in ICA Approach to Human Faces Recognition

By Celso Hilario, Josue-Rafael Montes, Teresa Hernández, Leonardo Barriga and Hugo Jiménez


Open access peer-reviewed

10. Application of Polynomial Spline Independent Component Analysis to fMRI Data

By Atsushi Kawaguchi, Young K. Truong and Xuemei Huang


Open access peer-reviewed

11. Preservation of Localization Cues in BSS-Based Noise Reduction: Application in Binaural Hearing Aids

By Jorge I. Marin-Hurtado and David V. Anderson


Open access peer-reviewed

12. ICA Applied to VSD Imaging of Invertebrate Neuronal Networks

By Evan S. Hill, Angela M. Bruno, Sunil K. Vasireddi and William N. Frost


Open access peer-reviewed

13. ICA-Based Fetal Monitoring

By Rubén Martín-Clemente and José Luis Camargo-Olivares


Open access peer-reviewed

14. Advancements in the Time-Frequency Approach to Multichannel Blind Source Separation

By Ingrid Jafari, Roberto Togneri and Sven Nordholm


Open access peer-reviewed

15. A Study of Methods for Initialization and Permutation Alignment for Time-Frequency Domain Blind Source Separation

By Auxiliadora Sarmiento, Iván Durán, Pablo Aguilera and Sergio Cruces


Open access peer-reviewed

16. Blind Implicit Source Separation – A New Concept in BSS Theory

By Fernando J. Mato-Méndez and Manuel A. Sobreira-Seoane


Edited Volume and chapters are indexed in

  • Worldcat
  • OpenAIRE
  • Google Scholar
  • AZ ebsco
  • Base
  • CNKI

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