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

Research output: Contribution to journalArticlepeer-review

5 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 languageEnglish
Article number07B727
JournalJournal of Applied Physics
Volume111
Issue number7
DOIs
Publication statusPublished - 2012 Apr 1

ASJC Scopus subject areas

  • Physics and Astronomy(all)

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