Research of lmage Blind Separation Method Based on QPSO and ICA
[1]FAN Wenbing,XING Junyang,LI Haitao,et al.Research of lmage Blind Separation Method Based on QPSO and ICA[J].Journal of Zhengzhou University (Engineering Science),2012,33(03):106-109,112.[doi:10.3969/j.issn.1671-6833.2012.03.027]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
33卷
Number of periods:
2012 03
Page number:
106-109,112
Column:
Public date:
2012-05-10
- Title:
- Research of lmage Blind Separation Method Based on QPSO and ICA
- Keywords:
- independent component analysis; quantum particle swarm optimization; blind source separation; negentropy
- CLC:
- TN911.7
- DOI:
- 10.3969/j.issn.1671-6833.2012.03.027
- Abstract:
- In this paper, we introduce the independent Component Analysis ( ICA) and Quantum ParticleSwarm Optimization ( PS0 ) brielly. As the ordinary gradient algorithm of ICA technology is easy to fall into loeal optimum , we proposed quantum-behavior based particle swarm optimization and independent component a.nalysis for blind source separation combining new algorithms. This algorithm takes negative entropy as the ob.jeetive function of independent component analysis, replaces the ordinary gradient algorithm with QPSO algorithm and separates the instantaneous mixed signals, All the steps of this algorithm are given in this paper.Experiment is show that the proposed algorithm can effectively achieve the image of the blind source separation, Compared with other algorithms, this algorithm shows belter performance.
- References:
- -
- Similar References:
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Last Update:
1900-01-01