A DOUBLE TIME—SCALE CNN FOR SOLVING TWO-DIMENSIONAL NAVIER—STOKES EQUATIONS

A practical cellular neural network (CNN) approximation to the Navier–Stokes equation describing the viscous flow of incompressible fluids is presented. The implementation of the CNN templates based on a finite-difference discretization scheme, including the double-timescale CNN dynamics and the treatment of various types of boundary conditions are explained. The operation of the continuous-time model is demonstrated through several examples.