Abstract
An algorithm for modeling sparse impulse systems is proposed. The method works well for both sparse and nonsparse systems. However, it offers significant savings in computational costs when the system is nonsparse. The approach used in this method is to determine all the delay positions of the unknown system simultaneously and then use an LMS (least-mean-square) algorithm to adapt the gains at delays with significant impulse response, in parallel. This method is the parallel implementation of Y.F. Chen and D.M. Etter (1989), and hence will work faster than serial implementation. >
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