Simplified neural network equalizer with noise whitening function for GPRML system

Hisashi Osawa, Masaya Hino, Nobuhiko Shinohara, Yoshihiro Okamoto, Yasuaki Nakamura, Hiroaki Muraoka

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

A new design method of the simplified neural network equalizer (NNE) with the noise whitening function for a generalized partial response (GPR) channel is proposed. The long-term bit error rate performance of GPR class-I maximum likelihood (GPR1ML) system employing NNE in perpendicular magnetic recording (PMR) channel with thermal decay is also obtained by computer simulation using our thermal decay model for a CoPtCr-SiO2 PMR medium with K uV/κT = 60. The performance of GPR1ML system with NNE (GPR1ML-NNE) is superior to that of GPR1ML with a transversal filter equalizer. The PR1ML system using a noise whitening NNE and a two-state Viterbi detector provides almost equivalent performance to that of GPR1ML-NNE having a 16-state detector.

Original languageEnglish
Pages (from-to)3777-3780
Number of pages4
JournalIEEE Transactions on Magnetics
Volume44
Issue number11 PART 2
DOIs
Publication statusPublished - 2008 Nov

Keywords

  • Generalized partial response class-I maximum likelihood (GPR1ML) system
  • Neural network equalizer
  • Perpendicular magnetic recording (PMR)
  • Thermal decay

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

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