离散时间细胞神经网络的收敛性条件

神经网络的收敛性是网络各种应用的基础。主要研究了离散细胞神经网络的收敛性 ,并给出了几个新的网络收敛性条件。如果细胞网络的模板不是互补的 ,则给出一个网络在细胞格子非相互作用演化方式下的收敛性结果 ,所获结果推广了已有的结论。如果模板是互补的 ,且是行占优的 ,则网络按细胞格子行方式进行演化是收敛的。如果模板是互补的 ,且是列占优的 ,则网络按细胞格子列方式进行演化是收敛的。

Study on the Convergence of Discrete-Time Cellular Neural Networks

The convergence of neural networks is known as the basis of various applications. In this paper, convergence of discrete-time cellular neural networks is studied and some new convergence conditions of the networks are given. If the template of the network is not reciprocal, a new convergence result of the networks with non-interacting evolution mode is given and the obtained result generalizes the existing result. If the template is reciprocal and row-dominant, the network is convergent in a row-wise evolution of the cell-grid. If the template is reciprocal and column-dominant, the network is convergent in a column-wise evolution of the cell-grid.;