Stability Analysis for Delayed Neural Networks Considering Both Conservativeness and Complexity | IEEE Journals & Magazine | IEEE Xplore

Stability Analysis for Delayed Neural Networks Considering Both Conservativeness and Complexity


Abstract:

This paper investigates delay-dependent stability for continuous neural networks with a time-varying delay. This paper aims at deriving a new stability criterion, conside...Show More

Abstract:

This paper investigates delay-dependent stability for continuous neural networks with a time-varying delay. This paper aims at deriving a new stability criterion, considering tradeoff between conservativeness and calculation complexity. A new Lyapunov-Krasovskii functional with simple augmented terms and delay-dependent terms is constructed, and its derivative is estimated by several techniques, including free-weighting matrix and inequality estimation methods. Then, the influence of the techniques used on the conservativeness and the complexity is analyzed one by one. Moreover, useful guidelines for improving criterion and future work are briefly discussed. Finally, the advantages of the proposed criterion compared with the existing ones are verified based on three numerical examples.
Page(s): 1486 - 1501
Date of Publication: 17 July 2015

ISSN Information:

PubMed ID: 26208366

Funding Agency:


References

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