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