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Neural Processing Letters
Erschienen in: Neural Processing Letters 1/2017

29.03.2016

Exponential Stability of Pseudo Almost Periodic Solutions for Cellular Neural Networks with Multi-Proportional Delays

verfasst von: Yuehua Yu

Erschienen in: Neural Processing Letters | Ausgabe 1/2017

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Abstract

This paper concerns with the pseudo almost periodic solutions for a class of cellular neural networks model with multi-proportional delays. By applying contraction mapping fixed point theorem and differential inequality techniques, we establish some sufficient conditions for the existence and exponential stability of pseudo almost periodic solutions for the model, which improve and supplement existing ones. Moreover, an example and its numerical simulation are given to support the theoretical results.
Vorheriger Artikel Pseudo Almost Automorphic Solutions of Recurrent Neural Networks with Time-Varying Coefficients and Mixed Delays
Nächster Artikel Semi-supervised Collective Classification in Multi-attribute Network Data

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Metadaten
Titel
Exponential Stability of Pseudo Almost Periodic Solutions for Cellular Neural Networks with Multi-Proportional Delays
verfasst von
Yuehua Yu
Publikationsdatum
29.03.2016
Verlag
Springer US
Erschienen in
Neural Processing Letters / Ausgabe 1/2017
Print ISSN: 1370-4621
Elektronische ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-016-9516-z

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