Multichannel blind deconvolution of non-minimum phase systems using information backpropagation

We present a novel method-filter decomposition approach, for multichannel blind deconvolution of non-minimum phase systems. In earlier work we developed an efficient natural gradient algorithm for causal FIR filters. In this paper we further study the natural gradient method for noncausal filters. We decompose the doubly finite filters into a product of two filters, a noncausal FIR filter and a causal FIR filter. The natural gradient algorithm is employed to train the causal FIR filter, and a novel information backpropagation algorithm is developed for training the noncausal FIR filter. Simulations are given to illustrate the effectiveness and validity of the algorithm.

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