Acta mathematica scientia,Series A
• Articles • Previous Articles Next Articles
Chen Wuhua; Lu Xiaomei; Li Qunhong; Guan Zhihong
Received:
Revised:
Online:
Published:
Contact:
Abstract: By using a technique of model transformation of the system, a new type of Lyapunov functional is introduced. By applying this new Lyapunov functional, a novel delay-dependent sufficient condition of exponential stability in mean square for stochastic Hopfield delay neural networks is derived in terms oflinear matrix inequalities (LMIs). A delay-independent sufficient condition is also presented. Numerical examples show that the proposed method is less conservative than the previous ones.
Key words: Stochastic Hopfield neural networks, Time-delay, Exponential stability in mean square, Linear matrix inequality (LMI)
CLC Number:
Chen Wuhua; Lu Xiaomei; Li Qunhong; Guan Zhihong. Exponential Stability in Mean Square for Stochastic Hopfield Delay Neural Networks: an LMI Approach[J].Acta mathematica scientia,Series A, 2007, 27(1): 109-117.
0 / / Recommend
Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks
URL: http://121.43.60.238/sxwlxbA/EN/
http://121.43.60.238/sxwlxbA/EN/Y2007/V27/I1/109
Condition of Reliable D Stability for a Class of Dynamic
Systems-an LMI Approach
The Effect of Time-Delay on the Asymptotic Behavior of theFood-limited Population Model
Cited
Rectangular Crouzeix-raviart Anisotropic Finite Element Method for Nonstationary Stokes Problem with Moving Grids
Boundedness of the Commutator of Marcinkiewicz Integral on Hardy Space and Herz-type Hardy Space