Performance enhancement of a radial basis function equalizer using nonlinear combining in digital magnetic storage channels

Research output: Contribution to journalConference article

Abstract

A multilayer perceptron RBFMLPEQ is proposed to enhance the performance of neural equalizer (NE) and to simplify the structure of RBFEQ. Through a simple simulation, it is shown that the RBFMLPEQ is capable of augmenting the performance of bit error ratio of NE and also has almost equal or superior performance compared to that of RBFEQ which is equal to Bayesian equalizer.

Original languageEnglish
Pages (from-to)AD-06
JournalDigests of the Intermag Conference
Publication statusPublished - 1999 Dec 1
EventProceedings of the 1999 IEEE International Magnetics Conference 'Digest of Intermag 99' - Kyongju, South Korea
Duration: 1999 May 181999 May 21

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Magnetic storage
Equalizers
Multilayer neural networks

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

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title = "Performance enhancement of a radial basis function equalizer using nonlinear combining in digital magnetic storage channels",
abstract = "A multilayer perceptron RBFMLPEQ is proposed to enhance the performance of neural equalizer (NE) and to simplify the structure of RBFEQ. Through a simple simulation, it is shown that the RBFMLPEQ is capable of augmenting the performance of bit error ratio of NE and also has almost equal or superior performance compared to that of RBFEQ which is equal to Bayesian equalizer.",
author = "Sooyong Choi and Daesik Hong",
year = "1999",
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language = "English",
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AU - Hong, Daesik

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N2 - A multilayer perceptron RBFMLPEQ is proposed to enhance the performance of neural equalizer (NE) and to simplify the structure of RBFEQ. Through a simple simulation, it is shown that the RBFMLPEQ is capable of augmenting the performance of bit error ratio of NE and also has almost equal or superior performance compared to that of RBFEQ which is equal to Bayesian equalizer.

AB - A multilayer perceptron RBFMLPEQ is proposed to enhance the performance of neural equalizer (NE) and to simplify the structure of RBFEQ. Through a simple simulation, it is shown that the RBFMLPEQ is capable of augmenting the performance of bit error ratio of NE and also has almost equal or superior performance compared to that of RBFEQ which is equal to Bayesian equalizer.

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