Equalization using the bilinear recursive polynomial perceptron with decision feedback

Research output: Contribution to conferencePaper

4 Citations (Scopus)

Abstract

In order to improve the performance and simplify the structure of the equalizer using bilinear recursive polynomial perceptron (BRPE), a new equalizer, which is a equalizer using bilinear recursive polynomial perceptron with decision feedback (BRPDFE), is proposed. The proposed BRPDFE is compared with the BRPE in terms of mean square error (MSE). And the performance is compared with the conventional decision feedback equalizer (DFE), the multilayer perceptron decision feedback equalizer (MLPDFE) and the BRPE in terms of bit-error rate (BER) in two data transmission systems. One is a digital communication system in which the dominant distortion factor is intersymbol interference (ISI). And the other is a digital storage system in which the primary interference element is nonlinear distortion. The results from analysis and simulation show that the proposed BRPDFE is superior to the other equalizers. Moveover, the BRPDFE has the simpler structure than the other equalizers.

Original languageEnglish
Pages366-371
Number of pages6
Publication statusPublished - 2000 Jan 1
EventInternational Joint Conference on Neural Networks (IJCNN'2000) - Como, Italy
Duration: 2000 Jul 242000 Jul 27

Other

OtherInternational Joint Conference on Neural Networks (IJCNN'2000)
CityComo, Italy
Period00/7/2400/7/27

Fingerprint

Equalizers
Polynomials
Neural networks
Feedback
Decision feedback equalizers
Digital communication systems
Nonlinear distortion
Digital storage
Intersymbol interference
Multilayer neural networks
Mean square error
Bit error rate
Data communication systems

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

Cite this

Choi, S., & Hong, D. (2000). Equalization using the bilinear recursive polynomial perceptron with decision feedback. 366-371. Paper presented at International Joint Conference on Neural Networks (IJCNN'2000), Como, Italy, .
Choi, Sooyong ; Hong, Daesik. / Equalization using the bilinear recursive polynomial perceptron with decision feedback. Paper presented at International Joint Conference on Neural Networks (IJCNN'2000), Como, Italy, .6 p.
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Choi, S & Hong, D 2000, 'Equalization using the bilinear recursive polynomial perceptron with decision feedback', Paper presented at International Joint Conference on Neural Networks (IJCNN'2000), Como, Italy, 00/7/24 - 00/7/27 pp. 366-371.

Equalization using the bilinear recursive polynomial perceptron with decision feedback. / Choi, Sooyong; Hong, Daesik.

2000. 366-371 Paper presented at International Joint Conference on Neural Networks (IJCNN'2000), Como, Italy, .

Research output: Contribution to conferencePaper

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AB - In order to improve the performance and simplify the structure of the equalizer using bilinear recursive polynomial perceptron (BRPE), a new equalizer, which is a equalizer using bilinear recursive polynomial perceptron with decision feedback (BRPDFE), is proposed. The proposed BRPDFE is compared with the BRPE in terms of mean square error (MSE). And the performance is compared with the conventional decision feedback equalizer (DFE), the multilayer perceptron decision feedback equalizer (MLPDFE) and the BRPE in terms of bit-error rate (BER) in two data transmission systems. One is a digital communication system in which the dominant distortion factor is intersymbol interference (ISI). And the other is a digital storage system in which the primary interference element is nonlinear distortion. The results from analysis and simulation show that the proposed BRPDFE is superior to the other equalizers. Moveover, the BRPDFE has the simpler structure than the other equalizers.

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Choi S, Hong D. Equalization using the bilinear recursive polynomial perceptron with decision feedback. 2000. Paper presented at International Joint Conference on Neural Networks (IJCNN'2000), Como, Italy, .