Introduction: Independent Component Analysis
R. Ganesh · InTech eBooks · 2012
IntroductionConsider a situation in which we have a number of sources emitting signals which are interfering with one another.Familiar situations in which this occurs are a crowded room with many people speaking at the same time, interfering electromagnetic waves from mobile phones or crosstalk from brain waves originating from different areas of the brain.In each of these situations the mixed signals are often incomprehensible and it is of interest to separate the individual signals.This is the goal of Blind Source Separation (BSS).A classic problem in BSS is the cocktail party problem.The objective is to sample a mixture of spoken voices, with a given number of microphones -the observations, and then separate each voice into a separate speaker channel -the sources.The BSS is unsupervised and thought of as a black box method.In this we encounter many problems, e.g.time delay between microphones, echo, amplitude difference, voice order in speaker and underdetermined mixture signal.Herault and Jutten Herault, J. & Jutten, C. (1987) proposed that, in a artificial neural network like architecture the separation could be done by reducing redundancy between signals.This approach initially lead to what is known as independent component analysis today.The fundamental research involved only a handful of researchers up until 1995.It was not until then, when Bell and Sejnowski Bell & Sejnowski (1995) published a relatively simple approach to the problem named infomax, that many became aware of the potential of Independent component analysis (ICA).Since then a whole community has evolved around ICA, centralized around some large research groups and its own ongoing conference, International Conference on independent component analysis and blind signal separation.ICA is used today in many different applications, e.g.medical signal analysis, sound separation, image processing, dimension reduction, coding and text analysis Azzerboni et al. (2004); Bingham et al. (2002); Cichocki & Amari (2002); De Martino et al. (2007); Enderle et al. (2005); James & Hesse (2005);