Advanced Search

Query:

Fill in the form and click »Search«...

Format:

Display: entries per page entries

Zbl 0995.92007
He, Huang; Cao, Jinde; Wang, Jun
Global exponential stability and periodic solutions of recurrent neural networks with delays. (English)
[J] Phys. Lett., A 298, No.5-6, 393-404 (2002). ISSN 0375-9601

Summary: By utilizing the Lyapunov functional method and applying M-matrix and topological degree theory, we analyze the global exponential stability and the existence of periodic solutions of a class of recurrent neural networks with delays. Some simple and new sufficient conditions ensuring existence, uniqueness and global exponential stability of the equilibrium point and periodic solutions of delayed recurrent neural networks are obtained, which do not require the activation functions to be differentiable, bounded and monotone nondecreasing. In addition, two examples are also given to illustrate the theory.

MSC 2000:: *92B20 General theory of neural networks
34K20 Stability theory of functional-differential equations
34K13 Periodic solutions of functional differential equations

Keywords: Lyapunov functional method; M-matrix; topological degree theory

Comment on this Item PDF MathML XML ASCII DVI PS BibTeX Online Ordering Article Journal

	Scientific prize winners of the ICM 2010
	Overhang
	Lie groups, physics and geometry. An introduction for physicists, engineers and chemists.

Advanced Search

Zentralblatt MATH Berlin [Germany]