对称神经元网络：渐近稳定性和学习

本文在分析对称神经元网络的渐近稳定性基础上,提出了一种非约束优化学习算法,保证训练样本成为稳定吸引子,具有一定大小的吸引域.理论上,我们证明了算法的收敛性以及形成的吸引域下界.计算机实验结果充分说明了学习算法的优越性.

Symmetric Neural Network: Asymptotic Stability and Learning

In this paper,we present an unconstrained optimal learning rule by analyzing asymptotic stability of the symmetric neural network. It ensures to store each training pattern with a nontrivial basin of attraction. Theoretically, we study convergence theorem of the learning algorithm and a lower bound of attraction basin. Computer simulations are reported to show its advantages.