Robust Stability Analysis of Neutral-Type Hybrid Bidirectional Associative Memory Neural Networks with Time-Varying Delays

Joint Authors

Feng, Wei
Yang, Simon X.
Wu, Haixia

Source

Abstract and Applied Analysis

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-05-27

Country of Publication

Egypt

No. of Pages

12

Main Subjects

Mathematics

Abstract EN

The global asymptotic robust stability of equilibrium is considered for neutral-type hybrid bidirectional associative memory neural networks with time-varying delays and parameters uncertainties.

The results we obtained in this paper are delay-derivative-dependent and establish various relationships between the network parameters only.

Therefore, the results of this paper are applicable to a larger class of neural networks and can be easily verified when compared with the previously reported literature results.

Two numerical examples are illustrated to verify our results.

American Psychological Association (APA)

Feng, Wei& Yang, Simon X.& Wu, Haixia. 2014. Robust Stability Analysis of Neutral-Type Hybrid Bidirectional Associative Memory Neural Networks with Time-Varying Delays. Abstract and Applied Analysis،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1033833

Modern Language Association (MLA)

Feng, Wei…[et al.]. Robust Stability Analysis of Neutral-Type Hybrid Bidirectional Associative Memory Neural Networks with Time-Varying Delays. Abstract and Applied Analysis No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-1033833

American Medical Association (AMA)

Feng, Wei& Yang, Simon X.& Wu, Haixia. Robust Stability Analysis of Neutral-Type Hybrid Bidirectional Associative Memory Neural Networks with Time-Varying Delays. Abstract and Applied Analysis. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1033833

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1033833