"Source Separation using ICA" by P. Shivani Sahoo, A. Barik et al.

Home > IJIPVS > Vol. 2 > Iss. 1 (2013)

International Journal of Image Processing and Vision Science

Article Title

Authors

P. Shivani Sahoo, ECE Dept.,ITER,BhubaneswarFollow
A. Barik, ECE Dept.,ITER,BhubaneswarFollow
Padmini Mishra, Dept. Of ECE., GIET, Gunupur, Odisha, IndiaFollow

Abstract

Independent Component Analysis (ICA) is a statistical signal processing technique having emerging new practical application areas, such as blind signal separation such as mixed voices or images, analysis of several types of data or feature extraction. Fast independent component analysis (Fast ICA ) is one of the most efficient ICA technique. Fast ICA algorithm separates the independent sources from their mixtures by measuring non-gaussianity.In this paper we present a method that can separate the signals as individual channels from other channels and also remove the noise using fast ica algorithm. The method is to decompose a multi channel signal into statistically independent components.

Recommended Citation

Sahoo, P. Shivani; Barik, A.; and Mishra, Padmini (2013) "Source Separation using ICA," International Journal of Image Processing and Vision Science: Vol. 2 : Iss. 1 , Article 10.
Available at: https://www.interscience.in/ijipvs/vol2/iss1/10

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