Title :
Designing cellular neural networks for the evaluation of local Boolean functions
Author :
Galias, Zbigniew
Author_Institution :
Dept. of Electr. Eng., Univ. of Min. & Metall., Cracow, Poland
fDate :
3/1/1993 12:00:00 AM
Abstract :
Describes general methods for designing a cellular neural network implementing an arbitrary Boolean function defined on the r-neighborhood. This is achieved by operating the network with time-variant templates as a cellular automaton that processes only binary inputs. These methods are suitable for solving local tasks. As an example, testing minimal distances is discussed
Keywords :
Boolean functions; cellular automata; neural nets; binary inputs; cellular automaton; cellular neural networks; local Boolean functions; local tasks; minimal distances; r-neighborhood; time-variant templates; Automata; Boolean functions; Cellular networks; Cellular neural networks; Circuit testing; Design methodology; Equations; Large-scale systems; Nonlinear circuits; Very large scale integration;
Journal_Title :
Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on
