Global Exponential Robust Stability of Static Interval Neural Networks with Time Delay in the Leakage Term

Joint Authors

Wang, Linshan
Chen, Guiying

Source

Journal of Applied Mathematics

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-6, 6 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-01-12

Country of Publication

Egypt

No. of Pages

6

Main Subjects

Mathematics

Abstract EN

The stability of a class of static interval neural networks with time delay in the leakage term is investigated.

By using the method of M-matrix and the technique of delay differential inequality, we obtain some sufficient conditions ensuring the global exponential robust stability of the networks.

The results in this paper extend the corresponding conclusions without leakage delay.

An example is given to illustrate the effectiveness of the obtained results.

American Psychological Association (APA)

Chen, Guiying& Wang, Linshan. 2014. Global Exponential Robust Stability of Static Interval Neural Networks with Time Delay in the Leakage Term. Journal of Applied Mathematics،Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-512570

Modern Language Association (MLA)

Chen, Guiying& Wang, Linshan. Global Exponential Robust Stability of Static Interval Neural Networks with Time Delay in the Leakage Term. Journal of Applied Mathematics No. 2014 (2014), pp.1-6.
https://search.emarefa.net/detail/BIM-512570

American Medical Association (AMA)

Chen, Guiying& Wang, Linshan. Global Exponential Robust Stability of Static Interval Neural Networks with Time Delay in the Leakage Term. Journal of Applied Mathematics. 2014. Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-512570

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-512570