Set-valued derivative and Lyapunov method for full-range cellular neural networks

Author

Marco, M. Di ; Forti, M. ; Grazzini, M. ; Pancioni, L.

Author_Institution

Dept. of Inf. Eng., Univ. of Siena, Rome, Italy

fYear

2009

fDate

24-27 May 2009

Firstpage

2705

Lastpage

2708

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.

Keywords

Lyapunov methods; cellular neural nets; convergence; differential equations; set theory; Lyapunov method; convergence analysis; differential variational inequality; full-range cellular neural network; set-valued derivative; Cellular neural networks; Electronic mail; Hypercubes; Lyapunov method; Neurons; Page description languages; Stability; State-space methods; Symmetric matrices; Very large scale integration;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 2009. ISCAS 2009. IEEE International Symposium on

Conference_Location

Taipei

Print_ISBN

978-1-4244-3827-3

Electronic_ISBN

978-1-4244-3828-0

Type

conf

DOI

10.1109/ISCAS.2009.5118360

Filename

5118360