DocumentCode :
1693287
Title :
A novel PSO based adaptive channel equalizer using a modified ANN structure
Author :
Yogi, Sandhya ; Subhashini, K.R. ; Satapathy, J.K. ; Kumar, Shiv
Author_Institution :
Dept. Of Electr. Engg, NIT, Rourkela, India
fYear :
2010
Firstpage :
442
Lastpage :
446
Abstract :
Here we have presented an alternate ANN structure called functional link ANN (FLANN) for channel equalization. In contrast to a feed forward ANN structure i.e. a multilayer perceptron (MLP), the FLANN is basically a single layer structure in which non-linearity is introduced by enhancing the input pattern with nonlinear function expansion. A novel method of training the FLANNs using PSO Algorithm is described. The neuron structure is modified to improve the performance of the equalizer. From the results it can be noted that the proposed structure improves the classification capability of the FLANNs in differentiating the received data.
Keywords :
adaptive equalisers; channel estimation; multilayer perceptrons; nonlinear functions; FLANN; PSO based adaptive channel equalizer algorithm; channel equalization; classification capability; feed forward ANN structure; functional link ANN; multilayer perceptron; neuron structure; nonlinear function expansion; single layer structure; Artificial neural networks; Bit error rate; Chebyshev approximation; Equalizers; Mathematical model; Neurons; Signal to noise ratio; Adaptive channel Equalization; Functional link Artificial Neural Network; Neural Network; PSO;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communication Control and Computing Technologies (ICCCCT), 2010 IEEE International Conference on
Conference_Location :
Ramanathapuram
Print_ISBN :
978-1-4244-7769-2
Type :
conf
DOI :
10.1109/ICCCCT.2010.5670592
Filename :
5670592
Link To Document :
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