三维转动神经网络的研究（1）能量函数

A Study of the Three-dimensional-rotational Neural Networks (1)Energy Function

简述了三维转动神经网络模型，通过对能量函数的研究，证明了网络当神经元个数远大于存贮图象数时，存贮图象为能量空间中的极小值．引入了绝热近似，有效局域场能正确迭代的几率，等于方向角和旋转角分别能正确选代的几率的乘积．

After simply introducing the three-dimensional-rotational neural networks model, the energy function is studied. The energies of the stored patterns are minima in the casethe neurons number is much more larger than that of the stored patterns. With the adiabatic approximation, the probability of correct retrieval of the local field is equal to the multiplication of the probabilities of correct retrieval of the direction angle and the rotation angles.