## Journal of Applied Mathematics

### Global Robust Attractive and Invariant Sets of Fuzzy Neural Networks with Delays and Impulses

#### Abstract

A class of fuzzy neural networks (FNNs) with time-varying delays and impulses is investigated. With removing some restrictions on the amplification functions, a new differential inequality is established, which improves previouse criteria. Applying this differential inequality, a series of new and useful criteria are obtained to ensure the existence of global robust attracting and invariant sets for FNNs with time-varying delays and impulses. Our main results allow much broader application for fuzzy and impulsive neural networks with or without delays. An example is given to illustrate the effectiveness of our results.

#### Article information

Source
J. Appl. Math., Volume 2013 (2013), Article ID 935491, 8 pages.

Dates
First available in Project Euclid: 14 March 2014

https://projecteuclid.org/euclid.jam/1394807898

Digital Object Identifier
doi:10.1155/2013/935491

Zentralblatt MATH identifier
1266.92006

#### Citation

Zhao, Kaihong; Wang, Liwenjing; Liu, Juqing. Global Robust Attractive and Invariant Sets of Fuzzy Neural Networks with Delays and Impulses. J. Appl. Math. 2013 (2013), Article ID 935491, 8 pages. doi:10.1155/2013/935491. https://projecteuclid.org/euclid.jam/1394807898

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