title: Global robust stability criteria for interval delayed full-range cellular neural networks.
abstract: This brief considers a class of delayed full-range (FR) cellular neural networks (CNNs) with uncertain interconnections between neurons modeled by means of intervalized matrices. Using mathematical tools from the theory of differential inclusions, a fundamental result on global robust stability of standard (S) CNNs is extended to prove global robust exponential stability for the corresponding class (same interconnection weights and inputs) of FR-CNNs. The result is of theoretical interest since, in general, the equivalence between the dynamical behavior of FR-CNNs and S-CNNs is not guaranteed.
authors.affiliation: Dipartimento di Ingegneria dell’Informazione, Università di Siena, Siena 53100, Italy. dimarco@dii.unisi.it
authors.forename: Mauro
authors.initials: M
authors.lastname: Di Marco
authors.forename: Massimo
authors.initials: M
authors.lastname: Grazzini
authors.forename: Luca
authors.initials: L
authors.lastname: Pancioni
mesh_terms: D000818:Animals; D003198:Computer Simulation; D006801:Humans; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D013997:Time Factors