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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
  3. Altmetric Badge
    Chapter 2 Blind Source Separation Based on Dictionary Learning: A Singularity-Aware Approach
  4. Altmetric Badge
    Chapter 3 Performance Study for Complex Independent Component Analysis
  5. Altmetric Badge
    Chapter 4 Blind Source Separation
  6. Altmetric Badge
    Chapter 5 Frequency Domain Blind Source Separation Based on Independent Vector Analysis with a Multivariate Generalized Gaussian Source Prior
  7. Altmetric Badge
    Chapter 6 Sparse Component Analysis: A General Framework for Linear and Nonlinear Blind Source Separation and Mixture Identification
  8. Altmetric Badge
    Chapter 7 Underdetermined Audio Source Separation Using Laplacian Mixture Modelling
  9. Altmetric Badge
    Chapter 8 Itakura-Saito Nonnegative Matrix Two-Dimensional Factorizations for Blind Single Channel Audio Separation
  10. Altmetric Badge
    Chapter 9 Source Localization and Tracking: A Sparsity-Exploiting Maximum a Posteriori Based Approach
  11. Altmetric Badge
    Chapter 10 Statistical Analysis and Evaluation of Blind Speech Extraction Algorithms
  12. Altmetric Badge
    Chapter 11 Speech Separation and Extraction by Combining Superdirective Beamforming and Blind Source Separation
  13. Altmetric Badge
    Chapter 12 On the Ideal Ratio Mask as the Goal of Computational Auditory Scene Analysis
  14. Altmetric Badge
    Chapter 13 Monaural Speech Enhancement Based on Multi-threshold Masking
  15. Altmetric Badge
    Chapter 14 REPET for Background/Foreground Separation in Audio
  16. Altmetric Badge
    Chapter 15 Nonnegative Matrix Factorization Sparse Coding Strategy for Cochlear Implants
  17. Altmetric Badge
    Chapter 16 Exploratory Analysis of Brain with ICA
  18. Altmetric Badge
    Chapter 17 Supervised Normalization of Large-Scale Omic Datasets Using Blind Source Separation
  19. Altmetric Badge
    Chapter 18 Feb ICA: Feedback Independent Component Analysis for Complex Domain Source Separation of Communication Signals
  20. Altmetric Badge
    Chapter 19 Semi-blind Functional Source Separation Algorithm from Non-invasive Electrophysiology to Neuroimaging
  21. Altmetric Badge
    Chapter 20 Erratum to: Performance Study for Complex Independent Component Analysis
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • Average Attention Score compared to outputs of the same age and source

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Article details
Title
Blind Source Separation
Published by
Signals and Communication Technology, 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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Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 May 2022.
All research outputs
#7,201,555
of 34,089,221 outputs
Outputs from Signals and Communication Technology
#15
of 64 outputs
Outputs of similar age
#70,130
of 374,593 outputs
Outputs of similar age from Signals and Communication Technology
#4
of 7 outputs
Altmetric has tracked 34,089,221 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 64 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one has done well, scoring higher than 76% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 374,593 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.