异步四元数神经网络模型的能量函数研究

An Investigation of the Energy Function of the Sequential Hamilton Number Neural Network

本文证明了异步离散四元数神经网络模型在其动力学演化过程中，网络的能量函数单调递减，网络最终将稳定在一个平衡态上，存贮图像在能量函数空间中对应一能量极小点，为网络的稳定吸引子。

In this paper) it is demonstrated that the energy of the random sequential Hamilton number neural network model decreases monotonously with time and so the network must end up in a state of equilibrium, the stored patterns are local minima of the energy function and are stable attractors of the network.