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

机译:二维磁记录的读/写通道建模和二维神经网络均衡

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摘要

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.
机译:提出了一种利用离散Voronoi图对具有非磁性晶界的离散粒状介质进行精确介质建模的方法,用于二维磁记录。还提出了一种双屏蔽阅读器灵敏度函数的简单封闭形式表示形式,用于对阅读过程进行建模。此外,提出了一种二维神经网络均衡器(2D-NNE),以减轻轨迹间干扰和类似抖动的介质噪声的影响。基于所提出的读/写通道模型,通过计算机仿真,获得了具有2D-NNE的部分响应I类最大似然(PR1ML)系统的误码率性能。该性能远远优于带有二维有限脉冲响应均衡器的PR1ML系统。

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