Minimal Resource Allocation Network (MRAN) for magnetic recording channel equalization

This paper presents the performance results of a recently developed minimal radial basis function neural network referred to as Minimal Resource Allocation Network (MRAN) for equalization of a highly nonlinear magnetic recording data storage channel. Using a realistic magnetic channel model, MRAN equalizer's performance has been studied in the presence of channel impairments alike partial erasure, additive white gaussian noise and jitter and width variance. Compared with the earlier neural equalizers, MRAN equalizer has better performance in terms of higher Signal to Distortion Ratios (SDR).