Triple-integral method for the stability analysis of delayed neural networks

2013 ◽  
Vol 99 ◽  
pp. 283-289 ◽  
Author(s):  
Zixin Liu ◽  
Jian Yu ◽  
Daoyun Xu ◽  
Dingtao Peng
Keyword(s):  
Neural Networks ◽  
Stability Analysis ◽  
Integral Method ◽  
Delayed Neural Networks ◽  
The Stability

On the stability analysis of delayed neural networks systems

2001 ◽  
Vol 14 (9) ◽  
pp. 1181-1188 ◽  
Author(s):  
Chunhua Feng ◽  
Réjean Plamondon
Keyword(s):  
Neural Networks ◽  
Stability Analysis ◽  
Delayed Neural Networks ◽  
The Stability

Exponential Stability Analysis for Neutral Stochastic Delayed Neural Networks

2011 ◽  
Vol 354-355 ◽  
pp. 877-880
Author(s):  
Min Gang Hua ◽  
Jun Tao Fei ◽  
Wei Li Dai
Keyword(s):  
Neural Networks ◽  
Stability Analysis ◽  
Exponential Stability ◽  
Lyapunov Functional ◽  
Stability Criteria ◽  
Delayed Neural Networks ◽  
The Stability ◽  
Delay Dependent ◽  
Delay Dependent Stability

In this paper, the generalized Finsler lemma and augmented Lyapunov functional are introduced to establish some improved delay-dependent stability criteria of neutral stochastic delayed neural networks. The stability criteria in the new results improve and generalize existing ones. Two examples are included to show the effectiveness of the results.

scholarly journals Stability of Sets Criteria for Impulsive Cohen-Grossberg Delayed Neural Networks with Reaction-Diffusion Terms

Mathematics ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 27 ◽  
Author(s):  
Gani Stamov ◽  
Stefania Tomasiello ◽  
Ivanka Stamova ◽  
Cvetelina Spirova
Keyword(s):  
Neural Networks ◽  
Stability Analysis ◽  
Asymptotic Stability ◽  
Equilibrium State ◽  
Global Exponential Stability ◽  
Lyapunov Method ◽  
Reaction Diffusion ◽  
Delayed Neural Networks ◽  
The Stability ◽  
Impulsive Reaction

The paper proposes an extension of stability analysis methods for a class of impulsive reaction-diffusion Cohen-Grossberg delayed neural networks by addressing a challenge namely stability of sets. Such extended concept is of considerable interest to numerous systems capable of approaching not only one equilibrium state. Results on uniform global asymptotic stability and uniform global exponential stability with respect to sets for the model under consideration are established. The main tools are expansions of the Lyapunov method and the comparison principle. In addition, the obtained results for the uncertain case contributed to the development of the stability theory of uncertain reaction-diffusion Cohen-Grossberg delayed neural networks and their applications. Moreover, examples are given to demonstrate the feasibility of our results.

A Survey of Fractional-Order Neural Networks

2017 ◽  
Author(s):  
Shuo Zhang ◽  
YangQuan Chen ◽  
Yongguang Yu
Keyword(s):  
Neural Networks ◽  
Stability Analysis ◽  
Fractional Order ◽  
Computational Science ◽  
General Introduction ◽  
Analysis Methods ◽  
Recent Trends ◽  
The Stability

In this paper, the literature of fractional-order neural networks is categorized and discussed, which includes a general introduction and overview of fractional-order neural networks. Various application areas of fractional-order neural networks have been found or used, and will be surveyed and summarized such as neuroscience, computational science, control and optimization. Recent trends in dynamics of fractional-order neural networks are presented and discussed. The results, especially the stability analysis of fractional-order neural networks, are reviewed and different analysis methods are compared. Furthermore, the challenges and conclusions of fractional-order neural networks are given.

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