模糊BAM神经网络的稳定性.pdfVIP

英文摘要 thesis is organized as follows: Chapter 1 introduces the background, research status of this issue , the content and the main results of this thesis. Chapter 2 introduces exponential stability of a class of fuzzy BAM neural networks with distributed delays, some sufficient conditions ensuring existence uniqueness and exponential stability of equilibrium point, which makes use of contraction mapping principle, Lyapunov functional and the nature of the activation functions. An example is given to demonstrate the effectiveness of the obtained results. Chapter 3 introduces global exponential stability of a class of fuzzy BAM neural networks with variable delays. By using the fixed point theorem, Halanay-type inequalities. A delay-independent sufficient condition for equilibrium point is obtained. A numerical example is given to illustrate the effectiveness of the results we have obstained. Chapter 4 introduces global asymptotic stability of a class of fuzzy BAM neural networks with distributed delays and reaction-diffusion terms. A sufficient condition is obtained by using the Lyapunov functional and the analysis technique. A numerical example is given to show the effectiveness of our analysis. Keyword: Stability of fuzzy BAM neural networks; Lyapunov functional; Halanay-type inequalities; Delays; Reaction-diffusion terms. IV 绪论 第一章 绪 论 §1.1 模型结构及产生的背景 神经网络是由许多简单的处理元——神经元构成的新型动力系统，它具有结 构可变性，巨能并行性，高度非线性，分布存储性，自学习性及自组织性等特点， 因此它能解决常规的信息处理方法无法解决或难以解决的问题。 1987 年，Kosko 将单层单向记忆神经网络推广到一种双层双向联想记忆神 经网络（Bi-direction Associate Memory ，这里