Applying genetic algorithm to modeling nonlinear transfer functions

A genetic algorithm (GA) technique for the approximation of nonlinear transfer functions is proposed in this paper. It is shown that the GA approximation method gives better accuracy than the classical Chebyshev approximation, which is sometimes considered to be the best one on the minimax criterion. Application of this technique to behavioral-level simulation is also discussed.