Exploiting piecewise linear features: multinested and simplicial cellular neural/nonlinear networks

This paper is especially written for a special session devoted to piecewise linear (PWL) circuits and systems to be presented in ISCAS 2003. We focus on applications of PWL functions to cellular neural/nonlinear networks (CNN). Much of the CNN functionality relies on the design of the nonlinear differential equation that rules the behavior of the cell. Accordingly, in this paper we present some of the latest developments in PWL CNN cell design. We describe and compare two novel architectures developed recently, namely, the multinested CNN and the simplicial CNN (S-CNN).