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Hybrid ANN reducing training time requirements and decision delay for equalization in presence of co-channel interference.

Authors :
Panigrahi, Siba Prasada
Nayak, Santanu Kumar
Padhy, Sasmita Kumari
Source :
Applied Soft Computing; Sep2008, Vol. 8 Issue 4, p1536-1538, 3p
Publication Year :
2008

Abstract

Abstract: Bayesian equalizer is known to be the optimum equalizer. This paper proposes a Hybrid Artificial Neural Network (Hybrid ANN) and an algorithm to modify Decision Feedback Equalizer (DFE) function of Bayesian equalizer while equalizing in presence of co-channel interference (CCI). A combination of Artificial Neural Network and Decision Feedback Equalizer (DFE) is termed as Neural-DFE (NDFE). The results show that the decision delay and training time requirement reduces significantly by use of NDFE. This creates an advantage specifically for a mobile environment where the CCI is varying in nature and the Bayesian equalizer requires a lot of training time. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
15684946
Volume :
8
Issue :
4
Database :
Supplemental Index
Journal :
Applied Soft Computing
Publication Type :
Academic Journal
Accession number :
34085552
Full Text :
https://doi.org/10.1016/j.asoc.2007.12.001