Title :
Fixed points incompatibility in neural networks with local interactions
Author_Institution :
Istituto di Elettronica, Perugia Univ., Italy
fDate :
6/1/1995 12:00:00 AM
Abstract :
Two conditions of incompatibility between fixed points are proved, which hold for a wide class of discrete-time, discrete-state, nonlinear neural networks with local interactions and no self-feedback. These conditions, which can be checked easily by inspection, can be stated briefly as follows: Let the network be defined on a two-dimensional array. A pair of states cannot both be fixed points of the network dynamics if: (1) in the neighborhood of a different component, there is no other different component; and (2) in the neighborhood of an equal component, there is no other equal component
Keywords :
cellular neural nets; discrete time systems; nonlinear network analysis; different component; discrete-state networks; discrete-time networks; equal component; fixed points incompatibility; local interactions; network dynamics; nonlinear neural networks; two-dimensional array; Associative memory; Cellular neural networks; Character generation; Image processing; Inspection; Intelligent networks; Neural networks; Pattern recognition; Polynomials; Very large scale integration;
Journal_Title :
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on