Article

Delay-Dependent Exponential Stability for Uncertain Stochastic Hopfield Neural Networks With Time-Varying Delays

Sch. of Autom., Nanjing Univ. of Sci. & Technol., Nanjing
Circuits and Systems I: Regular Papers, IEEE Transactions on (impact factor: 1.97). 07/2009; DOI:10.1109/TCSI.2008.2008499 pp.1241 - 1247
Source: IEEE Xplore

ABSTRACT This paper provides new delay-dependent conditions that guarantee the robust exponential stability of stochastic Hopfield type neural networks with time-varying delays and parameter uncertainties. Both the cases of the time-varying delays which are differentiable and may not be differentiable are considered. The stability conditions are derived by using the recently developed free-weighting matrices technique and expressed in terms of linear matrix inequalities. Numerical examples are provided to demonstrate the effectiveness of the proposed stability criteria. It is shown that the proposed stability results are less conservative than some previous ones in the literature.

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Keywords

developed free-weighting matrices technique
 
linear matrix inequalities
 
new delay-dependent conditions
 
proposed stability criteria
 
proposed stability results
 
robust exponential stability
 
stability conditions
 
stochastic Hopfield type neural networks