Further analysis of stability of uncertain neural networks with multiple time delays

Advances in Difference Equations

Sabri Arik¹ 

[1] Department of Electrical and Electronics Engineering, Isik University, Sile, Turkey

关键词: stability analysis;    delayed neural networks;    interval matrices;    Lyapunov functionals;   

DOI  :  10.1186/1687-1847-2014-41

学科分类：数学（综合）

来源: SpringerOpen

【 摘 要 】

This paper studies the robust stability of uncertain neural networks with multiple time delays with respect to the class of nondecreasing activation functions. By using the Lyapunov functional and homeomorphism mapping theorems, we derive a new delay-independent sufficient condition the existence, uniqueness, and global asymptotic stability of the equilibrium point for delayed neural networks with uncertain network parameters. The condition obtained for the robust stability establishes a matrix-norm relationship between the network parameters of the neural system, and therefore it can easily be verified. We also present some constructive numerical examples to compare the proposed result with results in the previously published corresponding literature. These comparative examples show that our new condition can be considered as an alternative result to the previous corresponding literature results as it defines a new set of network parameters ensuring the robust stability of delayed neural networks.

【 授权许可】

CC BY