Neural net equalization for a magnetic recording channel

In this paper, we summarize some recent results on the use of neural net equalization in a magnetic recording channel using partial response signaling. Specifically, we compare the performance of various neural net equalizers to the performance of more conventional equalizer designs. The results, which were based on experimentally measured data (includes both known and unknown nonlinear channel characteristics), show that with respect to a mean square error performance metric, the neural net equalizer has significantly better performance than conventional designs