An Artificial Immune Network Approach for Pattern Recognition

The discrete models and learning algorithms of artificial immune network are adopted. The mechanism of artificial immune system is combine with the framework of artificial neural network. The method of RBF neural network should be improved for fitting to any complicated system. An algorithm of artificial immune network for pattern recognition is introduced. The parameter-tuned problems are mainly explored about the basis functions; and a formulation is induced. The precision of pattern identifying is greatly improved. When a typical function is used as the simulation object, the experiment results illustrate this algorithm with high accuracy and convergence speed.

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