Waveform equalizer using a neural network

Abstract

A waveform equalizer for equalizing a distorted signal, contains a sampling unit, a time series generating unit, and an equalization neural network unit. The sampling unit samples the level of a distorted signal at a predetermined rate. The time series generating unit serially receives the sampled level and outputs in parallel a predetermined number of the levels which have been last received. The equalization neural network unit receives the outputs of the time series generating unit, and generates an equalized signal of the distorted signal based on the outputs of the time series generating unit using a set of equalization network weights which are preset therein. The waveform equalizer may further contain a distortion characteristic detecting unit, an equalization network weight holding unit, and a selector unit. The distortion characteristic detecting unit detects a distortion characteristic of the distorted signal. The equalization network weight holding unit holds a plurality of sets of equalization network weights each for being set in the equalization neural network unit. The selector unit selects one of the plurality of sets of equalization network weights according to the distortion characteristic which is detected in the distortion characteristic detecting unit, and supplies the selected set in the equalization neural network unit to set the selected set therein.