A decision feedback recurrent neural equalizer for digital communication

Sunghwan Ong, Sooyong Choi, Cheolwoo You, Daesik Hong

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

An important problem in high density digital magnetic recording system is that of channel equalization, that is, removal of distortions introduced by linear or nonlinear message corrupting mechanisms in the reconstruction of the original symbols. Severe nonlinear distortions in high density digital magnetic recording systems can make it difficult for conventional equalizers to reconstruct the originally recorded symbols. In this paper, we propose a Decision Feedback Recurrent Neural Equalizer (DFRNE) with a simple structure, which can recover the original symbols correctly under severe nonlinear distortion.

Original languageEnglish
Pages (from-to)2767-2769
Number of pages3
JournalIEEE Transactions on Magnetics
Volume33
Issue number5 PART 1
DOIs
Publication statusPublished - 1997

Bibliographical note

Funding Information:
Manuscript received February 4, 1997. This work was supported in part by a research grant of the university supporting program from the Ministry of Information & Communication and the Video Industrial R&D Association of Republic of Korea. e-mail : shong@catseye.yonsei.ac.kr

All Science Journal Classification (ASJC) codes

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

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