A search algorithm for the design of multinested cellular neural networks
Pedro Marcelo Julian, Radu Dogaru, Martin Haenggi, Leon Ong Chua · 2003
In this paper, we propose a search algorithm that can be used to effectively find multinested cellular neural networks (CNN) implementations for Boolean functions in high dimensional input spaces. For the purposes of this paper, the algorithm is illustrated for the five-dimensional case, although it is completely general and can be applied to find functions with an arbitrary number of inputs. Preliminary results for the 4-bit parameter resolution case are presented.