Blind source separation using modified contrast function in fastICA algorithm | Zendy

Alka Mahajan | Zendy; Gajanan K. Birajdar | Zendy

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Blind source separation using modified contrast function in fastICA algorithm

Author(s) -

Alka Mahajan,

Gajanan K. Birajdar

Publication year - 2010

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/1069-1397

Subject(s) - fastica , computer science , blind signal separation , contrast (vision) , algorithm , separation (statistics) , independent component analysis , source separation , function (biology) , artificial intelligence , pattern recognition (psychology) , machine learning , telecommunications , channel (broadcasting) , evolutionary biology , biology

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.

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