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(07B727) A study on modeling of the writing process and two-dimensional neural network equalization for two-dimensional magnetic recording

机译:(07B727)二维磁记录写入过程与二维神经网络均衡的建模研究

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A simple writing process considering magnetic clusters due to exchange coupling between grains is studied for two-dimensional magnetic recording. The bit error rate (BER) performance of a low-density parity-check coding and iterative decoding system with a two-dimensional neural network equalizer (2D-NNE) that can diminish the influences of jitter-like medium noise and inter-track interference is obtained using a read/write channel model based on the proposed writing process, and it is compared with those for one- and two-dimensional finite impulse response equalizers (FTREs). It is clarified that the BER performance for the 2D-NNE is far superior to those for the FTREs.
机译:考虑由于晶粒之间的交换耦合引起的磁簇的简单写入过程是针对二维磁记录。具有二维神经网络均衡器(2D-NNE)的低密度奇偶校验编码和迭代解码系统的误码率(BER)性能可以减少抖动样中噪声和轨道间干扰的影响使用基于所提出的写入过程使用读/写信道模型获得,并且与用于单维和二维有限脉冲响应均衡器(FTRES)的响应均衡器(FTRES)进行比较。澄清说,2D-NNE的BER性能远远优于该FTRES。

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