Pruned feed-forward networks for efficient implementation of multiple FIR filters with arbitrary frequency responses

Abstract

A new algorithm is presented for efficient implementation of multiple FIR filters in real-time applications. We introduce an analogy between the multiple FIR filters and linear feedforward networks, and show how the FIR filters with any frequency characteristics may be designed by a learning algorithm of the network with proper choice of training patterns. Starting from a fully-connected feed-forward architecture, more efficient network architectures may be obtainable by pruning connection weights with minor contributions. For demonstration we design feed-forward networks for 16 bandpass cochlear filters with much less connection weights and moderate performance degradation.