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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
Publication
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
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Neural Networks and Bioengineering
Keyword:
RBF neural networks,
natural immune system,
immune operation,
channel equalization,
Full Text: PDF(437.9KB)
Summary:
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.
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