Global Robust Exponential Dissipativity for Interval Recurrent Neural Networks with Infinity Distributed Delays
Joint Authors
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-06-13
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
This paper is concerned with the robust dissipativity problem for interval recurrent neural networks (IRNNs) with general activation functions, and continuous time-varying delay, and infinity distributed time delay.
By employing a new differential inequality, constructing two different kinds of Lyapunov functions, and abandoning the limitation on activation functions being bounded, monotonous and differentiable, several sufficient conditions are established to guarantee the global robust exponential dissipativity for the addressed IRNNs in terms of linear matrix inequalities (LMIs) which can be easily checked by LMI Control Toolbox in MATLAB.
Furthermore, the specific estimation of positive invariant and global exponential attractive sets of the addressed system is also derived.
Compared with the previous literatures, the results obtained in this paper are shown to improve and extend the earlier global dissipativity conclusions.
Finally, two numerical examples are provided to demonstrate the potential effectiveness of the proposed results.
American Psychological Association (APA)
Wang, Xiaohong& Qi, Huan. 2013. Global Robust Exponential Dissipativity for Interval Recurrent Neural Networks with Infinity Distributed Delays. Abstract and Applied Analysis،Vol. 2013, no. 2013, pp.1-16.
https://search.emarefa.net/detail/BIM-482872
Modern Language Association (MLA)
Wang, Xiaohong& Qi, Huan. Global Robust Exponential Dissipativity for Interval Recurrent Neural Networks with Infinity Distributed Delays. Abstract and Applied Analysis No. 2013 (2013), pp.1-16.
https://search.emarefa.net/detail/BIM-482872
American Medical Association (AMA)
Wang, Xiaohong& Qi, Huan. Global Robust Exponential Dissipativity for Interval Recurrent Neural Networks with Infinity Distributed Delays. Abstract and Applied Analysis. 2013. Vol. 2013, no. 2013, pp.1-16.
https://search.emarefa.net/detail/BIM-482872
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-482872