Advanced Search

Query:

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

Format:

Display: entries per page entries

Zbl 1121.34078
Ren, Fengli; Cao, Jinde
LMI-based criteria for stability of high-order neural networks with time-varying delay. (English)
[J] Nonlinear Anal., Real World Appl. 7, No. 5, 967-979 (2006). ISSN 1468-1218

The authors consider a class of high-order neural networks with time-varying delay of the form $$ x^{\prime}_i(t) = -a_i x_i(t) +{\sum}_{j=1}^Lw_{ij}{\Pi}_{k\in I_j}[g_k(x_k(t))]^{d_k(j)} + {\sum}_{j=1}^Lw_{ij}^{\tau}{\Pi}_{k\in I_j}[g_k(x_k(t-\tau (t)))]^{d_k(j)} $$ for $i=1,2,\dots, n$. Under appropriate assumptions this system has a unique equilibrium point. Additional sufficient conditions for the global exponential stability of the equilibrium point are formulated. Some numerical examples are given to illustrate the theoretical results.
[Gheorghe Moroşanu (Budapest)]

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

Keywords: global exponential stability; Lyapunov functional

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]