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

Masato Yamashita; Yoshihiro Okamoto; Yasuaki Nakamura; Hisashi Osawa; Kenji Miura; S. Greaves; H. Aoi; Y. Kanai; Hiroaki Muraoka

doi:10.1063/1.3680535

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

Masato Yamashita, Yoshihiro Okamoto, Yasuaki Nakamura, Hisashi Osawa, Kenji Miura, S. Greaves, H. Aoi, Y. Kanai, Hiroaki Muraoka

Broadband Engineering Division

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

Abstract

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 (FIREs). It is clarified that the BER performance for the 2D-NNE is far superior to those for the FIREs.

Original language	English
Article number	07B727
Journal	Journal of Applied Physics
Volume	111
Issue number	7
DOIs	https://doi.org/10.1063/1.3680535
Publication status	Published - 2012 Apr 1

ASJC Scopus subject areas

Physics and Astronomy(all)

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10.1063/1.3680535

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title = "A study on modeling of the writing process and two-dimensional neural network equalization for two-dimensional magnetic recording",

abstract = "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 (FIREs). It is clarified that the BER performance for the 2D-NNE is far superior to those for the FIREs.",

author = "Masato Yamashita and Yoshihiro Okamoto and Yasuaki Nakamura and Hisashi Osawa and Kenji Miura and S. Greaves and H. Aoi and Y. Kanai and Hiroaki Muraoka",

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AU - Yamashita, Masato

AU - Okamoto, Yoshihiro

AU - Nakamura, Yasuaki

AU - Osawa, Hisashi

AU - Miura, Kenji

AU - Greaves, S.

AU - Aoi, H.

AU - Kanai, Y.

AU - Muraoka, Hiroaki

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

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