Cellular neural network design with continuous signals
S. Schwarz, Wolfgang M. Mathis · 2003
Basic design methods for the class of cellular neural networks (CNNs) with continuous input signals are introduced. The realistic model of CNNs proposed by L.O. Chua and L. Yang (1988) combines components of the Hopfield-net, cellular automata, and of cellular systems. The CNN design methods integrate special conditions for technical architectures with respect to real-time implementations. Hacijan's polynomial solution method is applied to solve the set of linear inequalities which correspond with the CNN design.>