Numerical solutions of distributed diffusion Hopfield neural network equations

摘要

A finite element method for numerical solutions of the systems governed by distributed models of Hopfield-type neural network equations is studied. When time keeps continuous and the spatial dimension is one, a semi-discrete algorithm for numerical solutions using quadratic interpolation functions is constructed, in which the Gauss–Legendre quadrature of numerical integrations of nonlinear term and Runge–Kutta method for solving ordinary differential equation are efficiently used. Finally, numerical simulations results obtained by Mathematica to show the scheme is stable.