A Novel Criterion for Global Asymptotic Stability of Neutral-Type Neural Networks with Discrete Time Delays

2018 ◽  
pp. 353-360
Author(s):  
Ozlem Faydasicok ◽  
Sabri Arik
Keyword(s):  
Neural Networks ◽  
Asymptotic Stability ◽  
Discrete Time ◽  
Global Asymptotic Stability ◽  
Time Delays ◽  
Neutral Type

scholarly journals An Analysis of Stability of a Class of Neutral-Type Neural Networks with Discrete Time Delays

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Zeynep Orman ◽  
Sabri Arik
Keyword(s):  
Asymptotic Stability ◽  
Discrete Time ◽  
Global Asymptotic Stability ◽  
Time Delays ◽  
Neutral Type ◽  
Sufficient Conditions ◽  
Type Systems ◽  
Neural System ◽  
Network Parameters ◽  
Analysis Of Stability

The problem of existence, uniqueness, and global asymptotic stability is considered for the class of neutral-type neural network model with discrete time delays. By employing a suitable Lyapunov functional and using the homeomorphism mapping theorem, we derive some new delay-independent sufficient conditions for the existence, uniqueness, and global asymptotic stability of the equilibrium point for this class of neutral-type systems. The obtained conditions basically establish some norm and matrix inequalities involving the network parameters of the neural system. The main advantage of the proposed results is that they can be expressed in terms of network parameters only. Some comparative examples are also given to compare our results with the previous corresponding results and demonstrate the effectiveness of the results presented.

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