An Invariance Algorithm of Synergetic Pattern Recognition Based  on Conjugate Gradient Method of Alternant Iterative

Invariance method is an important aspect of Synergetic Pattern Recognition research. Usually there are deformation between test pattern and prototype pattern. A Synergetic invariance algorithm is proposed in this paper,which is based on alternant iterative match. The question of match is converted to question of function optimization in Synergetic Neural Network(SNN), A potential energy function optimization algorithm which based on conjugate gradient method is proposed, and the optimum parameters of test pattern and affine transform are gotten by the way of alternant iteration. The nationalization of test pattern is equivalent to nationalization of prototype pattern in SNN. The right pattern can be gotten by the dynamic evolvement of order parameter. The algorithm is similar to the recognition of human being compared with the traditional frequency field method which utilized by the Fourier transform. And the algorithm can avoid the pseudo-state of potential dynamical evolution compared with the method based on gradient dynamics. The validity and robustness of the algorithm are demonstrated by the experiments.