Research Article
Article:Blind source separation using modified contrast function in fastICA algorithm
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 6 - Issue 4 |
| Published: September 2010 |
| Authors: Dr. Alka Mahajan, Gajanan Birajdar |
10.5120/1069-1397
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Dr. Alka Mahajan, Gajanan Birajdar . Article:Blind source separation using modified contrast function in fastICA algorithm. International Journal of Computer Applications. 6, 4 (September 2010), 14-17. DOI=10.5120/1069-1397
@article{ 10.5120/1069-1397,
author = { Dr. Alka Mahajan,Gajanan Birajdar },
title = { Article:Blind source separation using modified contrast function in fastICA algorithm },
journal = { International Journal of Computer Applications },
year = { 2010 },
volume = { 6 },
number = { 4 },
pages = { 14-17 },
doi = { 10.5120/1069-1397 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2010
%A Dr. Alka Mahajan
%A Gajanan Birajdar
%T Article:Blind source separation using modified contrast function in fastICA algorithm%T
%J International Journal of Computer Applications
%V 6
%N 4
%P 14-17
%R 10.5120/1069-1397
%I Foundation of Computer Science (FCS), NY, USA
Abstract
A novel contrast function is proposed to be used in fastICA algorithm for Blind Source Separation (BSS). Simulation results show that the proposed nonlinear function used to separate image mixtures, results in faster execution and good quality image separation. Peak Signal to Noise Ratio (PSNR), Improved Signal to Noise Ratio (ISNR), Signal to Noise Ratio (SNR) and Root Mean Square Error (RMSE) are used to evaluate quality of separated images and Amari error is calculated to prove the performance of separation quality.
References
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