Simplification of neural network equalizer for perpendicular magnetic recording

Hisashi Osawa, Toshimasa Shimizu, Takumi Nakaoka, Yoshihiro Okamoto, Hidetoshi Saito, Hiroaki Muraoka, Yoshihisa Nakamura

研究成果: Article査読

2 被引用数 (Scopus)

抄録

In this paper, we examine neural network equalization in a perpendicular magnetic recording channel with jitter medium noise and MR nonlinear distortion. First, we propose simplifying a neural network equalizer by using a hybrid genetic algorithm. Next, we determine the bit error rate of a PR2ML method provided with the simplified neural network equalizer and compare it to those of a conventional neural network equalizer and a transversal filter equalizer. The results were improvements of about 0.8 and 2.0 dB in the SNR of the PR2ML method using the simplified neural network equalizer compared to the conventional neural network equalizer and the transversal filter equalizer, respectively.

本文言語English
ページ(範囲)19-27
ページ数9
ジャーナルElectronics and Communications in Japan, Part II: Electronics (English translation of Denshi Tsushin Gakkai Ronbunshi)
89
2
DOI
出版ステータスPublished - 2006 2 1

ASJC Scopus subject areas

  • 物理学および天文学(全般)
  • コンピュータ ネットワークおよび通信
  • 電子工学および電気工学

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