改进的自组织神经网络算法的收敛性(Ⅱ)

Convergence of improved learning algorithm based on self-organization neural network (Ⅱ)

对自组织神经网络改进算法的收敛性进行了证明。当该算法中的参数和网络权值初始值选取适当小的正实数时，网络收敛。文中并分析了该算法的收敛性与网络参数、初始值之间的关系。

The convergence of the improved algorithm based on the self-organization neuralnetwork for dynamic nonlinear system identification is proved in this paper. The algorithm isstable if the network has suitable initial weight values and low positive-real parameters. Thenthe relation between convergence of the network and the initial values of the network is analyzed.