Blind separation of sources: A nonlinear neural algorithm

In many signal processing applications, the signals provided by the sensors are mixtures of many sources. The problem of separation of sources is to extract the original signals from these mixtures. A new algorithm, based on ideas of backpropagation learning, is proposed for source separation. No a priori information on the sources themselves is required, and the algorithm can deal even with non-linear mixtures. After a short overview of previous works in that eld, we will describe the proposed algorithm. Then, some experimental results will be discussed.