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Enhancing linear independent component analysis : comparison of various metaheuristic methods
Joint Authors
Salman, Husayn Muhammad
Abbas, Nida A.
Source
The Iraqi Journal of Electrical and Electronic Engineering
Issue
Vol. 16, Issue 1 (30 Jun. 2020), pp.113-122, 10 p.
Publisher
University of Basrah College of Engineering
Publication Date
2020-06-30
Country of Publication
Iraq
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
Various methods have been exploited in the blind source separation problems, especially in cocktail party problems.
The most commonly used method is the independent component analysis (ICA).
Many linear and nonlinear ICA methods, such as the radial basis functions (RBF) and self-organizing map (SOM) methods utilise neural networks and genetic algorithms as optimisation methods.
For the contrast function, most of the traditional methods, especially the neural networks, use the gradient descent as an objective function for the ICA method.
Most of these methods trap in local minima and consume numerous computation requirements.
Three metaheuristic optimisation methods, namely particle, quantum particle, and glowworm swarm optimisation methods are introduced in this study to enhance the existing ICA methods.
The proposed methods exhibit better results in separation than those in the traditional methods according to the following separation quality measurements: signal-to-noise ratio, signal-to-interference ratio, log-likelihood ratio, perceptual evaluation speech quality and computation time.
These methods effectively achieved an independent identical distribution condition when the sampling frequency of the signals is 8 kHz.
American Psychological Association (APA)
Abbas, Nida A.& Salman, Husayn Muhammad. 2020. Enhancing linear independent component analysis : comparison of various metaheuristic methods. The Iraqi Journal of Electrical and Electronic Engineering،Vol. 16, no. 1, pp.113-122.
https://search.emarefa.net/detail/BIM-972158
Modern Language Association (MLA)
Abbas, Nida A.& Salman, Husayn Muhammad. Enhancing linear independent component analysis : comparison of various metaheuristic methods. The Iraqi Journal of Electrical and Electronic Engineering Vol. 16, no. 1 (Jun. 2020), pp.113-122.
https://search.emarefa.net/detail/BIM-972158
American Medical Association (AMA)
Abbas, Nida A.& Salman, Husayn Muhammad. Enhancing linear independent component analysis : comparison of various metaheuristic methods. The Iraqi Journal of Electrical and Electronic Engineering. 2020. Vol. 16, no. 1, pp.113-122.
https://search.emarefa.net/detail/BIM-972158
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 121-122
Record ID
BIM-972158