scholarly journals Modelling variability in full-field displacement profiles and Poisson ratio of wood in compression using stochastic neural networks

Silva Fennica ◽  
2009 ◽  
Vol 43 (5) ◽  
Author(s):  
Hong Ling ◽  
Sandhya Samarasinghe ◽  
G. Kulasiri
Keyword(s):  
Neural Networks ◽  
Poisson Ratio ◽  
Stochastic Neural Networks ◽  
Full Field ◽  
Field Displacement

Exponential Stability for Stochastic Neural Networks with Time-Varying Delay and Leakage Delay

2015 ◽  
Vol 742 ◽  
pp. 399-403
Author(s):  
Ya Jun Li ◽  
Jing Zhao Li
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Sufficient Conditions ◽  
Leakage Delay ◽  
Linear Matrix ◽  
Stochastic Neural Networks ◽  
Time Varying ◽  
Matrix Inequalities ◽  
Time Varying Delay ◽  
Varying Delay

This paper investigates the exponential stability problem for a class of stochastic neural networks with leakage delay. By employing a suitable Lyapunov functional and stochastic stability theory technic, the sufficient conditions which make the stochastic neural networks system exponential mean square stable are proposed and proved. All results are expressed in terms of linear matrix inequalities (LMIs). Example and simulation are presented to show the effectiveness of the proposed method.

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