关键词: 协同模式识别, 最优化方法, 协同势能函数, 记忆梯度法

Abstract: The traditional training method of synergetic pattern recognition is figured out adjoint vector from prototype vector according to certain rules for example pseudo-inverse or M-P generalized-inverse.The course is slowly to the high-dimension samples，and is not fit to the change of dimension.The studying of potential energy function dynamics process can train prototype vector and adjoint vector meanwhile.The optimization approach is introduced to synergetic dynamics evolution process，using the memory gradient algorithm instead of the steepest decent algorithm to get optimization prototype vector.The prototype vector experimental result on images shows that the new algorithm can effectively search the prototype vector and adjoint vector meanwhile，and excellent，correct and fast recognition result shows the new algorithm is more available than traditional training method.

Key words: synergetic pattern recognition, optimization method, synergetic potential energy function, memory gradient method