Abstract
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.
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