Exponential stability of stochastic Hopfield neural networks with distributed parameters
DENG Fei-qi
ZHAO Bi-tong
LUO Qi
Abstract：Based on stochastic Fubini theorem,the Hopfield neural network system depicted by a stochastic partial differential equation is translated into a stochastic ordinary differential equation. By constructing a mean Lyapunov function with respect to the space variables and using Ito formula under the integral operators, the exponential stability of stochastic neutral systems with distributed parameters is investigated by deviating of the function along the trajectories of the systems. Also, the Lyapunov exponent estimate is obtained. Thus, the stability of stochastic systems with distributed parameters is studied by Lyapunov direct method.
Keywords：Hopfield neural networksdistributed parameterLyapunov function
Publication Date：2005-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 196-200 )