Blind Signal Deconvolution by Spatio Temporal Decorrelation and Demixing
نویسندگان
چکیده
In this paper we present a simple efficient local unsupervised learning algorithm for on-line adaptive multichannel blind deconvolution and separation of i.i.d. sources. Under mild conditions, there exits a stable inverse system so that the source signals can be exactly recovered from their convolutive mixtures. Based on the existence of the inverse filter, we construct a two-stage neural network which consists of blind equalization and source separation. In blind equalization stage, we employ anti-Hebbian learning in temporal domain for decorrelation. For blind separation, we can apply any existing algorithms. Extensive computer simulations confirm the validity and high performance of our proposed learning algorithm.
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