↓ Skip to main content

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
Attention for Chapter 12: On the Ideal Ratio Mask as the Goal of Computational Auditory Scene Analysis
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Mentioned by

patent
2 patents

Readers on

mendeley
27 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Article details
Chapter title
On the Ideal Ratio Mask as the Goal of Computational Auditory Scene Analysis
Chapter number 12
Book title
Blind Source Separation
Published in
Signals and Communication Technology, 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

Login to access the Attention Digest and the Sentiment Analysis related to this output.

Timeline Attention over time Attention Score history
Login to access the full charts related to this output.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
United Kingdom 2 7%
Germany 1 4%
Unknown 24 89%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 9 33%
Student > Master 6 22%
Researcher 2 7%
Student > Postgraduate 2 7%
Student > Doctoral Student 1 4%
Other 1 4%
Unknown 6 22%
Readers by discipline
Readers by discipline Count As %
Computer Science 10 37%
Engineering 8 30%
Physics and Astronomy 2 7%
Arts and Humanities 1 4%
Biochemistry, Genetics and Molecular Biology 1 4%
Other 0 0%
Unknown 5 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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
#7,283,845
of 33,704,742 outputs
Outputs from Signals and Communication Technology
#17
of 65 outputs
Outputs of similar age
#97,182
of 450,178 outputs
Outputs of similar age from Signals and Communication Technology
#2
of 10 outputs
Altmetric has tracked 33,704,742 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 65 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one has gotten more attention than average, scoring higher than 72% 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 450,178 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 76% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 8 of them.