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Neural Processing Letters
Erschienen in: Neural Processing Letters 1/2014

01.08.2014

Periodic Solution for Fuzzy Cohen–Grossberg BAM Neural Networks with Both Time-Varying and Distributed Delays and Variable Coefficients

verfasst von: Wengui Yang

Erschienen in: Neural Processing Letters | Ausgabe 1/2014

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Abstract

In this paper, we investigate the existence and global exponential stability of periodic solution for a general class of fuzzy Cohen–Grossberg bidirectional associative memory (BAM) neural networks with both time-varying and (finite or infinite) distributed delays and variable coefficients. Some novel sufficient conditions for ascertaining the existence, uniqueness, global attractivity and exponential stability of the periodic solution to the considered system are obtained by applying matrix theory, inequality analysis technique and contraction mapping principle. The results remove the usual assumption that the activation functions are bounded and/or continuously differentiable. It is believed that these results are significant and useful for the design and applications of fuzzy Cohen–Grossberg BAM neural networks. Moreover, an example is employed to illustrate the effectiveness and feasibility of the results obtained here.
Vorheriger Artikel Global Robust Exponential Stability for Interval Delayed Neural Networks with Possibly Unbounded Activation Functions
Nächster Artikel Processing and Transmission of Confidence in Recurrent Neural Hierarchies

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Metadaten
Titel
Periodic Solution for Fuzzy Cohen–Grossberg BAM Neural Networks with Both Time-Varying and Distributed Delays and Variable Coefficients
verfasst von
Wengui Yang
Publikationsdatum
01.08.2014
Verlag
Springer US
Erschienen in
Neural Processing Letters / Ausgabe 1/2014
Print ISSN: 1370-4621
Elektronische ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-013-9310-0

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