摘要
离散Hopfield神经网络的稳定性不仅本身有重要的理论意义 ,而且也是网络应用的基础。主要研究非对称离散Hopfield神经网络在并行演化模式下的动力学行为 ,得到了一些新的稳定性条件 。
The stability of discrete Hopfield neural networks not only has an important theoretical significance, but also is the foundation of the applications of the networks. In this paper, the dynamic behavior of asymmetric discrete Hopfield neural network is studied mainly in parallel updating mode, and some new stability conditions of the neural networks are given. The obtained results serve the function of further generalizing some existing conclusions.
出处
《空军工程大学学报(自然科学版)》
CSCD
2004年第3期75-77,共3页
Journal of Air Force Engineering University(Natural Science Edition)
关键词
神经网络
并行演化
稳定性
能量函数
neural networks
parallel updating
stability
energy function