Permutation correction of filter bank ICA using static channel characteristics

Abstract

This paper exploits static channel characteristics to provide a precise solution to the permutation problem in filter bank approach to Independent Component Analysis (ICA). The filter bank approach combines the high accuracy of time domain ICA and the computational efficiency of frequency domain ICA. Decimation in each sub-band helps in better formulation of the directivity patterns. The nulls of the directivity patterns are dependent on the location of the source signals and this property is used for resolving the permutation problem. The experimental results, show a good behavior with reduced computational complexity and do not require non-stationarity of the signals.