Delay-Distribution-Dependent Exponential Stability Criteria for Discrete-Time Recurrent Neural Networks With Stochastic Delay

2008 ◽  
Vol 19 (7) ◽  
pp. 1299-1306 ◽  
Author(s):  
Dong Yue ◽  
Yijun Zhang ◽  
Engang Tian ◽  
Chen Peng
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Discrete Time ◽  
Recurrent Neural Networks ◽  
Stability Criteria ◽  
Stochastic Delay ◽  
Delay Distribution

CONVERGENCE OF DISCRETE-TIME RECURRENT NEURAL NETWORKS WITH VARIABLE DELAY

2005 ◽  
Vol 15 (02) ◽  
pp. 581-595 ◽  
Author(s):  
JINLING LIANG ◽  
JINDE CAO ◽  
JAMES LAM
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Discrete Time ◽  
Recurrent Neural Networks ◽  
Matrix Decomposition ◽  
Linear Matrix ◽  
Variable Delay ◽  
Stability Criteria ◽  
Lmi Approach ◽  
The Neural Networks

In this paper, some global exponential stability criteria for the equilibrium point of discrete-time recurrent neural networks with variable delay are presented by using the linear matrix inequality (LMI) approach. The neural networks considered are assumed to have asymmetric weighting matrices throughout this paper. On the other hand, by applying matrix decomposition, the model is embedded into a cooperative one, the latter possesses important order-preserving properties which are basic to our analysis. A sufficient condition is obtained ensuring the componentwise exponential stability of the system with specific performances such as decay rate and trajectory bounds.

scholarly journals Exponential Stability and Numerical Methods of Stochastic Recurrent Neural Networks with Delays

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Shifang Kuang ◽  
Yunjian Peng ◽  
Feiqi Deng ◽  
Wenhua Gao
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Recurrent Neural Networks ◽  
Sufficient Conditions ◽  
Mean Square ◽  
Stochastic Delay ◽  
Backward Euler ◽  
Inequality Techniques ◽  
The Stability ◽  
Stability In Mean Square

Exponential stability in mean square of stochastic delay recurrent neural networks is investigated in detail. By using Itô’s formula and inequality techniques, the sufficient conditions to guarantee the exponential stability in mean square of an equilibrium are given. Under the conditions which guarantee the stability of the analytical solution, the Euler-Maruyama scheme and the split-step backward Euler scheme are proved to be mean-square stable. At last, an example is given to demonstrate our results.

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