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