Blind Source Separation: Advances in Theory, Algorithms and Applications

✍ Scribed by Ganesh R. Naik, Wenwu Wang (eds.)

Publisher: Springer-Verlag Berlin Heidelberg
Year: 2014
Tongue: English
Leaves: 548
Series: Signals and Communication Technology
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

Blind Source Separation intends to report the new results of the efforts on the study of Blind Source Separation (BSS). The book collects novel research ideas and some training in BSS, independent component analysis (ICA), artificial intelligence and signal processing applications. Furthermore, the research results previously scattered in many journals and conferences worldwide are methodically edited and presented in a unified form. The book is likely to be of interest to university researchers, R&D engineers and graduate students in computer science and electronics who wish to learn the core principles, methods, algorithms and applications of BSS.

Dr. Ganesh R. Naik works at University of Technology, Sydney, Australia; Dr. Wenwu Wang works at University of Surrey, UK.

✦ Table of Contents

Front Matter....Pages i-ix
Front Matter....Pages 1-1
Quantum-Source Independent Component Analysis and Related Statistical Blind Qubit Uncoupling Methods....Pages 3-37
Blind Source Separation Based on Dictionary Learning: A Singularity-Aware Approach....Pages 39-59
Performance Study for Complex Independent Component Analysis....Pages 61-96
Subband-Based Blind Source Separation and Permutation Alignment....Pages 97-130
Frequency Domain Blind Source Separation Based on Independent Vector Analysis with a Multivariate Generalized Gaussian Source Prior....Pages 131-150
Sparse Component Analysis: A General Framework for Linear and Nonlinear Blind Source Separation and Mixture Identification....Pages 151-196
Underdetermined Audio Source Separation Using Laplacian Mixture Modelling....Pages 197-229
Itakura-Saito Nonnegative Matrix Two-Dimensional Factorizations for Blind Single Channel Audio Separation....Pages 231-257
Source Localization and Tracking: A Sparsity-Exploiting Maximum a Posteriori Based Approach....Pages 259-287
Front Matter....Pages 289-289
Statistical Analysis and Evaluation of Blind Speech Extraction Algorithms....Pages 291-322
Speech Separation and Extraction by Combining Superdirective Beamforming and Blind Source Separation....Pages 323-348
On the Ideal Ratio Mask as the Goal of Computational Auditory Scene Analysis....Pages 349-368
Monaural Speech Enhancement Based on Multi-threshold Masking....Pages 369-393
REPET for Background/Foreground Separation in Audio....Pages 395-411
Nonnegative Matrix Factorization Sparse Coding Strategy for Cochlear Implants....Pages 413-434
Exploratory Analysis of Brain with ICA....Pages 435-463
Supervised Normalization of Large-Scale Omic Datasets Using Blind Source Separation....Pages 465-497
Feb ICA: Feedback Independent Component Analysis for Complex Domain Source Separation of Communication Signals....Pages 499-519
Semi-blind Functional Source Separation Algorithm from Non-invasive Electrophysiology to Neuroimaging....Pages 521-551
Erratum to: Performance Study for Complex Independent Component Analysis....Pages E1-E1

✦ Subjects

Signal, Image and Speech Processing; Computer Imaging, Vision, Pattern Recognition and Graphics; Computational Intelligence; Biomedical Engineering; Computational Mathematics and Numerical Analysis

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