Paper Info
Title
Set-Valued Derivative And Lyapunov Method For Full-Range Cellular Neural Networks
Abstract
The paper proposes an alternate definition of set-valued derivative, with respect to that in a previous paper, for computing the evolution of a (candidate) Lyapunov function along the solutions of a class of differential variational inequalities (DVIs). The class of DVIs is of interest in that it includes as a special case the dynamics of full-range (FR) cellular neural networks (CNNs). The usefulness of the new definition is discussed in the context of a generalized Lyapunov method for addressing stability and convergence of solutions of DVIs and FR-CNNs.
Year
DOI
Venue
2009
10.1109/ISCAS.2009.5118360
ISCAS: 2009 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOLS 1-5
Keywords
Field
DocType
set theory,probability density function,stability,differential equations,hypercubes,cellular neural network,cellular neural networks,convergence,mathematical model,lyapunov function,very large scale integration,symmetric matrices,variational inequality,data mining
Convergence (routing),Lyapunov function,Differential equation,Applied mathematics,Set theory,Mathematical optimization,Control theory,Computer science,Symmetric matrix,Differential variational inequality,Cellular neural network,Variational inequality
Conference
Citations 
PageRank 
References 
0
0.34
4
Authors
4
Name
Order
Citations
PageRank
Mauro Di Marco120518.38
Mauro Forti239836.80
Massimo Grazzini313111.01
Luca Pancioni420717.58