A novel image recognition algorithm, Synergetic Neural Networks (SNN) based on immune clonal lgorithm, is proposed in this paper. The presented method introduces the global optimal searching ability of immune clonal select algorithm to construct data clustering algorithm, which used to solve the prototype vector in SNN. The simulation result of the Brodatz images and Synthetic Aperture Radar (SAR) images show the proposed algorithm can improve the performance of SNN as compared with the standard SNN and it can reduce greatly the training and test time leave the classification accuracy almost unchanged as compared with the traditional support vector machine.
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