2013Unpublished venueRequires access

Blind source separation: A review and analysis

Madhab Pal, Rajib Roy, Joyanta Basu, Milton S. Bepari

Open publisher page 66 citations

Abstract

Blind Source Separation (BSS) refers to a problem where both the sources and the mixing methodology are unknown, only mixture signals are available for further separation process. In several situations it is desirable to recover all individual sources from the mixed signal, or at least to segregate a particular source. In laboratory condition, most of the algorithms works very fine where input signals, no. of source present in the mixture, mixing methodology etc are well known to the separation process. But in real-life scenario the problem is much more complicated and it begins with the input signal, a mixture where most of the parameters are unknown. This paper will try to summarize those approaches taken previously to solve this problem and an experiment of source separation which will mix using Independent Component Analysis (ICA) and then de-mix those source signals using ICA as the basic/prime approach.

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What this paper is about

Blind Source Separation (BSS) refers to a problem where both the sources and the mixing methodology are unknown, only mixture signals are available for further separation process. In several situations it is desirable to recover all individual sources from the mixed signal, or at least to segregate a particular source. In laboratory condition, most of the algorithms works very fine where input signals, no. of source present in the mixture, mixing methodology etc are well known to the separation process. But in real-life scenario the problem is much more complicated and it begins with the input signal, a mixture where most of the parameters are unknown. This paper will try to summarize those approaches taken previously to solve this problem and an experiment of source separation which will mix using Independent Component Analysis (ICA) and then de-mix those source signals using ICA as the basic/prime approach.

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Available abstract

Blind Source Separation (BSS) refers to a problem where both the sources and the mixing methodology are unknown, only mixture signals are available for further separation process. In several situations it is desirable to recover all individual sources from the mixed signal, or at least to segregate a particular source. In laboratory condition, most of the algorithms works very fine where input signals, no. of source present in the mixture, mixing methodology etc are well known to the separation process. But in real-life scenario the problem is much more complicated and it begins with the input signal, a mixture where most of the parameters are unknown. This paper will try to summarize those approaches taken previously to solve this problem and an experiment of source separation which will mix using Independent Component Analysis (ICA) and then de-mix those source signals using ICA as the basic/prime approach.

Key concepts: Blind signal separation, Independent component analysis, Source separation, Computer science, Mixing (physics), SIGNAL (programming language), Process (computing), Separation process

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