Suboptimal bayesian equalizer using an nonlinear multilayer combiner

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2 Citations (Scopus)

Abstract

In order to reduce the complexity and enhance the performance of the Bayesian equalizer (REQ) using the radial basis function (RBF) network, a new equalizer (RNEQ) using the RBF network with a nonlinear multilayer combiner is proposed. The proposed RNEQ produces the output using nonlinear multilayer combiner. The RNEQ is applied to a digital communication system and a nonlinear magnetic storage system. From computer simulation results, the RNEQ with almost 70% reduced structure over the REQ shows nearly the same performance in a digital communication system. And in a nonlinear digital storage system the RNEQ is superior to the REQ. In addition, the RNEQ converges to lower mean squared error value than the other equalizers.

Original languageEnglish
Pages353-362
Number of pages10
Publication statusPublished - 1999 Dec 1
EventProceedings of the 1999 9th IEEE Workshop on Neural Networks for Signal Processing (NNSP'99) - Madison, WI, USA
Duration: 1999 Aug 231999 Aug 25

Other

OtherProceedings of the 1999 9th IEEE Workshop on Neural Networks for Signal Processing (NNSP'99)
CityMadison, WI, USA
Period99/8/2399/8/25

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All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Signal Processing
  • Software

Cite this

Choi, S., & Hong, D. (1999). Suboptimal bayesian equalizer using an nonlinear multilayer combiner. 353-362. Paper presented at Proceedings of the 1999 9th IEEE Workshop on Neural Networks for Signal Processing (NNSP'99), Madison, WI, USA, .