The classifiable function of the wavelet neural network(WNN) is studied in this paper

and an integration of the immune evolutionary algorithm and WNN is proposed

based on the model of the immune evolutionary wavelet neural network(IEWNN). In this model

the immune evolutionary algorithm(IEA) used for training the network is a globally parallel algorithm which integrates the immune and the evolutionary mechanisms.The IEA is conducive to alleviating the undulating phenomenon produced by the blind fold behaviors of the original operators in the existent evolutionary algorithms through adaptively learning form the evolutionary environment.The analysis in theory and simulations show that WNN based on IEA is not only feasible but also effective.Because IEA has the parallel operation rules

the intelligent searching behavior and the criterion based on probability

it is conducive to relaxing the conditions of applying WNN and improving the ability of association memory and information processing.