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Blind Source Separation

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Cover of 'Blind Source Separation'

Table of Contents

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    Book Overview
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    Chapter 1 Quantum-Source Independent Component Analysis and Related Statistical Blind Qubit Uncoupling Methods
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    Chapter 2 Blind Source Separation Based on Dictionary Learning: A Singularity-Aware Approach
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    Chapter 3 Performance Study for Complex Independent Component Analysis
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    Chapter 4 Blind Source Separation
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    Chapter 5 Frequency Domain Blind Source Separation Based on Independent Vector Analysis with a Multivariate Generalized Gaussian Source Prior
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    Chapter 6 Sparse Component Analysis: A General Framework for Linear and Nonlinear Blind Source Separation and Mixture Identification
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    Chapter 7 Underdetermined Audio Source Separation Using Laplacian Mixture Modelling
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    Chapter 8 Itakura-Saito Nonnegative Matrix Two-Dimensional Factorizations for Blind Single Channel Audio Separation
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    Chapter 9 Source Localization and Tracking: A Sparsity-Exploiting Maximum a Posteriori Based Approach
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    Chapter 10 Statistical Analysis and Evaluation of Blind Speech Extraction Algorithms
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    Chapter 11 Speech Separation and Extraction by Combining Superdirective Beamforming and Blind Source Separation
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    Chapter 12 On the Ideal Ratio Mask as the Goal of Computational Auditory Scene Analysis
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    Chapter 13 Monaural Speech Enhancement Based on Multi-threshold Masking
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    Chapter 14 REPET for Background/Foreground Separation in Audio
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    Chapter 15 Nonnegative Matrix Factorization Sparse Coding Strategy for Cochlear Implants
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    Chapter 16 Exploratory Analysis of Brain with ICA
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    Chapter 17 Supervised Normalization of Large-Scale Omic Datasets Using Blind Source Separation
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    Chapter 18 Feb ICA: Feedback Independent Component Analysis for Complex Domain Source Separation of Communication Signals
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    Chapter 19 Semi-blind Functional Source Separation Algorithm from Non-invasive Electrophysiology to Neuroimaging
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    Chapter 20 Erratum to: Performance Study for Complex Independent Component Analysis
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Title
Blind Source Separation
Published by
Springer-Verlag Berlin Heidelberg, January 2014
DOI 10.1007/978-3-642-55016-4
ISBNs
978-3-64-255015-7, 978-3-64-255016-4, 978-3-66-251403-0
Editors

Ganesh R. Naik, Wenwu Wang

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 19%
Student > Master 6 19%
Student > Ph. D. Student 5 16%
Student > Doctoral Student 4 13%
Student > Bachelor 3 9%
Other 1 3%
Unknown 7 22%
Readers by discipline Count As %
Engineering 9 28%
Mathematics 3 9%
Computer Science 3 9%
Physics and Astronomy 2 6%
Chemical Engineering 1 3%
Other 2 6%
Unknown 12 38%