Channel equalization using complex extreme learning machine with RBF kernels

Authors:
Ming-Bin Li;Guang-Bin Huang;Paramasivan Saratchandran;Narasimhan Sundararajan
Affiliations:
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
Venue:
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
Year:
2006

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Abstract

This paper studies the performance of extreme learning machine with complex-valued radial basis function (ELM-CRBF) in the channel equalization applications. Comparing with complex minimal resource allocation network (CMRAN), complex radial basis function (CRBF) network and Bayesian equalizers, the simulation results show that ELM-CRBF equalizer is superior in terms of symbol error rate (SER) and learning speed.