Nonlinear multilayer combining techniques for bayesian equalizers using the radial basis function network as a digital magnetic storage equalizer

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

In order to reduce the complexity and enhance the performance of the Bayesian equalizer using the radial basis function (RBF) network, a new equalizer using the RBF network with a nonlinear multilayer combiner (RNEQ) is proposed. The RNEQ is applied to a digital storage system in which the primary element of impairment is nonlinear distortion due to partial erasure. From computer simulation results, the RNEQ with almost 70% reduced structural complexity over the conventional equalizer using RBF network has nearly the same performance in terms of bit-error rate (BER) and mean squared error.

Original languageEnglish
Pages (from-to)2319-2321
Number of pages3
JournalIEEE Transactions on Magnetics
Volume35
Issue number5 PART 1
DOIs
Publication statusPublished - 1999

Bibliographical note

Funding Information:
This work (97K3-0803-01-04-1) was supported in part by Korea Science and Engineering Foundation

All Science Journal Classification (ASJC) codes

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

Fingerprint

Dive into the research topics of 'Nonlinear multilayer combining techniques for bayesian equalizers using the radial basis function network as a digital magnetic storage equalizer'. Together they form a unique fingerprint.

Cite this