An Immunity-Based RBF Network and Its Application in Equalization of Nonlinear Time-Varying Channels

Xiaogang ZANG  Xinbao GONG  Ronghong JIN  Xiaofeng LING  Bin TANG  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E92-A   No.5   pp.1390-1394
Publication Date: 2009/05/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E92.A.1390
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Neural Networks and Bioengineering
RBF neural networks,  natural immune system,  immune operation,  channel equalization,  

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This paper proposes a novel RBF training algorithm based on immune operations for dynamic problem solving. The algorithm takes inspiration from the dynamic nature of natural immune system and locally-tuned structure of RBF neural network. Through immune operations of vaccination and immune response, the RBF network can dynamically adapt to environments according to changes in the training set. Simulation results demonstrate that RBF equalizer based on the proposed algorithm obtains good performance in nonlinear time-varying channels.