多稳态
平衡点
人工神经网络
Hopfield网络
乙状窦函数
数学
理论(学习稳定性)
李雅普诺夫函数
不动点定理
整数(计算机科学)
订单(交换)
常微分方程
固定点
功能(生物学)
应用数学
计算机科学
微分方程
拓扑(电路)
纯数学
数学分析
组合数学
非线性系统
人工智能
物理
财务
进化生物学
程序设计语言
经济
机器学习
量子力学
生物
作者
Zhongwen Wu,Xiaobing Nie,Boqiang Cao
标识
DOI:10.1016/j.neunet.2022.12.013
摘要
This paper investigates the coexistence and local stability of multiple equilibrium points for a class of competitive neural networks with sigmoidal activation functions and time-varying delays, in which fractional-order derivative and state-dependent switching are involved at the same time. Some novel criteria are established to ensure that such n-neuron neural networks can have [Formula: see text] total equilibrium points and [Formula: see text] locally stable equilibrium points with m1+m2=n, based on the fixed-point theorem, the definition of equilibrium point in the sense of Filippov, the theory of fractional-order differential equation and Lyapunov function method. The investigation implies that the competitive neural networks with switching can possess greater storage capacity than the ones without switching. Moreover, the obtained results include the multistability results of both fractional-order switched Hopfield neural networks and integer-order switched Hopfield neural networks as special cases, thus generalizing and improving some existing works. Finally, four numerical examples are presented to substantiate the effectiveness of the theoretical analysis.
科研通智能强力驱动
Strongly Powered by AbleSci AI