Read/Write Channel Modeling and Two-Dimensional Neural Network Equalization for Two-Dimensional Magnetic Recording

An accurate medium modeling method of discretized granular medium with non-magnetic grain boundaries using a discrete Voronoi diagram is proposed for two-dimensional magnetic recording. A simple closed-form representation of a double-shielded reader sensitivity function is also proposed for modeling the reading process. Moreover, a two-dimensional neural network equalizer (2D-NNE) is proposed to mitigate the influence of intertrack interference and jitter-like medium noise. The bit-error rate performance of partial response class-I maximum likelihood (PR1ML) system with the 2D-NNE is obtained by computer simulation based on the proposed read/write channel model. The performance is far superior to that of PR1ML system with a two-dimensional finite impulse response equalizer.