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A Class of Sequential Blind Source Separation Method in Order Using Swarm Optimization Algorithm
- Source :
- Circuits, Systems, and Signal Processing. 35:3220-3243
- Publication Year :
- 2015
- Publisher :
- Springer Science and Business Media LLC, 2015.
-
Abstract
- We consider the problem of sequential, blind source separation in some specific order from a mixture of sub- and sup-Gaussian sources. Three methods of separation are developed, specifically, kurtosis maximization using (a) particle swarm optimization, (b) differential evolution, and (c) artificial bee colony algorithm, all of which produce the separation in decreasing order of the absolute kurtosis based on the maximization of the kurtosis cost function. The validity of the methods was confirmed through simulation. Moreover, compared with other conventional methods, the proposed method separated the various sources with greater accuracy. Finally, we performed a real-world experiment to separate electroencephalogram (EEG) signals from a super-determined mixture with Gaussian noise. Whereas the conventional methods separate simultaneously EEG signals of interest along with noise, the result of this example shows the proposed methods recover from the outset solely those EEG signals of interest. This feature will be of benefit in many practical applications.
- Subjects :
- 0209 industrial biotechnology
business.industry
Applied Mathematics
Particle swarm optimization
Pattern recognition
02 engineering and technology
Maximization
Independent component analysis
Blind signal separation
Artificial bee colony algorithm
symbols.namesake
020901 industrial engineering & automation
Gaussian noise
Differential evolution
Signal Processing
0202 electrical engineering, electronic engineering, information engineering
Kurtosis
symbols
020201 artificial intelligence & image processing
Artificial intelligence
business
Mathematics
Subjects
Details
- ISSN :
- 15315878 and 0278081X
- Volume :
- 35
- Database :
- OpenAIRE
- Journal :
- Circuits, Systems, and Signal Processing
- Accession number :
- edsair.doi...........4987f16e459bdef25bdc535a767581a7