Exponential Stability of a Class of Stochastic Interval Cellular Neural Networks

The exponential stability of a class of stochastic interval cellular neural networks with delay is investigated in this paper. For such neural networks, a kind of equivalent description is given ,and several sufficient conditions for the exponential stability in the mean square and surely exponentia...

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Bibliographic Details
Main Authors: Jin-fang Han, Ji-qing Qiu
Format: Conference Proceeding
Language:English
Subjects:
Artificial intelligence
Cellular neural networks
Computational intelligence
Delay
Exponential Stability
formula
Indium tin oxide
Lyapunov function
Lyapunov method
Neural networks
Robust stability
Stability criteria
Stochastic interval Cellular Neural Networks
Stochastic processes
Sufficient conditions
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Summary:The exponential stability of a class of stochastic interval cellular neural networks with delay is investigated in this paper. For such neural networks, a kind of equivalent description is given ,and several sufficient conditions for the exponential stability in the mean square and surely exponential stability are established by the Lyapunov function method and lto formula. The criteria given here are generalizations of some provided in the earlier references.
DOI:10.1109/AICI.2009.483