LMI-Based Approach for Exponential Robust Stability of High-Order Hopfield Neural Networks with Time-Varying Delays

Joint Authors

Wang, Yangfan
Wang, Linshan

Source

Journal of Applied Mathematics

Issue

Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-8, 8 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2012-06-06

Country of Publication

Egypt

No. of Pages

8

Main Subjects

Mathematics

Abstract EN

This paper studies the problems of global exponential robust stability of high-order hopfield neural networks with time-varying delays.

By employing a new Lyapunov-Krasovskii functional and linear matrix inequality, some criteria of global exponential robust stability for the high-order neural networks are established, which are easily verifiable and have a wider adaptive.

American Psychological Association (APA)

Wang, Yangfan& Wang, Linshan. 2012. LMI-Based Approach for Exponential Robust Stability of High-Order Hopfield Neural Networks with Time-Varying Delays. Journal of Applied Mathematics،Vol. 2012, no. 2012, pp.1-8.
https://search.emarefa.net/detail/BIM-993015

Modern Language Association (MLA)

Wang, Yangfan& Wang, Linshan. LMI-Based Approach for Exponential Robust Stability of High-Order Hopfield Neural Networks with Time-Varying Delays. Journal of Applied Mathematics No. 2012 (2012), pp.1-8.
https://search.emarefa.net/detail/BIM-993015

American Medical Association (AMA)

Wang, Yangfan& Wang, Linshan. LMI-Based Approach for Exponential Robust Stability of High-Order Hopfield Neural Networks with Time-Varying Delays. Journal of Applied Mathematics. 2012. Vol. 2012, no. 2012, pp.1-8.
https://search.emarefa.net/detail/BIM-993015

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-993015