Modeling complex systems by reaction-diffusion cellular nonlinear networks with polynomial weight-functions

The treatment of reaction-diffusion differential equations leads to a description of various complex phenomena like nonlinear wave propagation or structure formation, in particular in biological systems. Reaction-diffusion cellular nonlinear networks (RD-CNN) can virtually represent any feature of reaction-diffusion systems. For RD-CNN it has been shown that the existence of locally active cells is a necessary condition for emergent complex behavior (Chua, 1998). In this contribution we use RD-CNN with polynomial reaction terms for modeling complex systems. First results for a RD-CNN modeling a FitzHugh-Nagumo system, with network parameters obtained by a supervised optimization process, are given.