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Blind Source Separation

Overview of attention for book
Cover of 'Blind Source Separation'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    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
Attention for Chapter 12: On the Ideal Ratio Mask as the Goal of Computational Auditory Scene Analysis
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Chapter title
On the Ideal Ratio Mask as the Goal of Computational Auditory Scene Analysis
Chapter number 12
Book title
Blind Source Separation
Published by
Springer Berlin Heidelberg, February 2016
DOI 10.1007/978-3-642-55016-4_12
Book ISBNs
978-3-64-255015-7, 978-3-64-255016-4
Authors

Christopher Hummersone, Toby Stokes, Tim Brookes, Hummersone, Christopher, Stokes, Toby, Brookes, Tim

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 8%
Germany 1 4%
Unknown 22 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 36%
Student > Master 6 24%
Student > Postgraduate 2 8%
Researcher 2 8%
Student > Bachelor 1 4%
Other 1 4%
Unknown 4 16%
Readers by discipline Count As %
Computer Science 10 40%
Engineering 8 32%
Physics and Astronomy 2 8%
Biochemistry, Genetics and Molecular Biology 1 4%
Arts and Humanities 1 4%
Other 0 0%
Unknown 3 12%