Neural realization of fast linear filters

Abstract

The paper presents a neural network architecture for linear filtering of signals based on a scheme for fast calculation of orthogonal transformations. Compared to the known standard filtering schemes the network offers high training efficiency accompanied by substantial simplicity of realization. Additionally, the same basic network topology enables realization of diverse transformations.