A Blind Separation Approach for Magnitude Bounded Sources
Alper Tunga Erdogan · 2006
A novel blind source separation approach for channels with and without memory is introduced. The proposed approach makes use of a pre-whitening procedure to convert the original convolutive channel into a lossless and memoryless one. Then, a blind subgradient algorithm, which corresponds to an l/sub /spl infin// norm based criterion, is used for the separation of sources. The proposed separation algorithm exploits the assumed boundedness of the original sources and it has a simple update rule. The typical performance of the algorithm is illustrated through simulation examples where separation is achieved with only small numbers of iterations.