Performance of RBF equalizer in data storage channels

Research output: Contribution to conferencePaper

2 Citations (Scopus)

Abstract

In order to compensate for severe intersymbol interference (ISI) and combat nonlinear distortions in digital magnetic recording systems, Bayesian equalizer using the radial basis function (RBF) network, REQ, is applied as a channel equalizer to a data storage system using partial erasure (PE) model. It can be seen from various computer simulation results that the REQ has more complex structure than conventional linear equalizer (LE) while the bit-error-ratio (BER) of the REQ is lower than that of the LE. Using various simulation parameters such as the width of the basis function, the updating algorithm for the centers in REQ, the recording density of a data storage system, Du, and so froth, the performance in terms of BER of the REQ is examined.

Original languageEnglish
Pages1077-1080
Number of pages4
Publication statusPublished - 1999 Dec 1
EventInternational Joint Conference on Neural Networks (IJCNN'99) - Washington, DC, USA
Duration: 1999 Jul 101999 Jul 16

Other

OtherInternational Joint Conference on Neural Networks (IJCNN'99)
CityWashington, DC, USA
Period99/7/1099/7/16

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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    Choi, S., & Hong, D. (1999). Performance of RBF equalizer in data storage channels. 1077-1080. Paper presented at International Joint Conference on Neural Networks (IJCNN'99), Washington, DC, USA, .