Pipelined Genetic Algorithm Initialized RAN Based RBF Modulation Classifier

Authors:
Fuqiang Xue;Lindong Ge;Bin Wang
Affiliations:
Zhengzhou Science & Technology Institute, Zhengzhou, China 450002;Zhengzhou Science & Technology Institute, Zhengzhou, China 450002;Zhengzhou Science & Technology Institute, Zhengzhou, China 450002
Venue:
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Year:
2009

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Abstract

Partitional clustering approaches have been used in initialization of resources allocation network (RAN). However, they are sensitive to the clustering number and susceptible to local optima. This paper proposes a new RAN initialization algorithm based on pipelined genetic algorithm. It initializes the hidden layer with much less centers and improves the performance of RAN with higher clustering validity as well as parsimonious structure. Simulation results show RBF modulation classifier trained with the new algorithm can get higher accuracy.