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Equilibrium analysis of non‐symmetric CNNs
Author(s) -
Arik Sabri,
Tavsanoglu Vedat
Publication year - 1996
Publication title -
international journal of circuit theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.364
H-Index - 52
eISSN - 1097-007X
pISSN - 0098-9886
DOI - 10.1002/(sici)1097-007x(199605/06)24:3<269::aid-cta915>3.0.co;2-l
Subject(s) - uniqueness , equilibrium point , exponential stability , cellular neural network , mathematics , saturation (graph theory) , point (geometry) , stability (learning theory) , artificial neural network , mathematical analysis , computer science , physics , combinatorics , artificial intelligence , nonlinear system , geometry , differential equation , quantum mechanics , machine learning
Two useful results concerning the equilibrium analysis of non‐symmetric cellular neural networks (CNNs) are presented. First a new sufficient condition ensuring the existence of a stable equilibrium point in the total saturation region is given. Then another condition which guarantees the uniqueness and global asymptotic stability of the equilibrium point is obtained.