Cargando…

Almost Periodic Dynamics for Memristor-Based Shunting Inhibitory Cellular Neural Networks with Leakage Delays

We investigate a class of memristor-based shunting inhibitory cellular neural networks with leakage delays. By applying a new Lyapunov function method, we prove that the neural network which has a unique almost periodic solution is globally exponentially stable. Moreover, the theoretical findings of...

Descripción completa

Detalles Bibliográficos
Autores principales: Lu, Lin, Li, Chaoling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5090130/
https://www.ncbi.nlm.nih.gov/pubmed/27840634
http://dx.doi.org/10.1155/2016/3587271
_version_ 1782464362455236608
author Lu, Lin
Li, Chaoling
author_facet Lu, Lin
Li, Chaoling
author_sort Lu, Lin
collection PubMed
description We investigate a class of memristor-based shunting inhibitory cellular neural networks with leakage delays. By applying a new Lyapunov function method, we prove that the neural network which has a unique almost periodic solution is globally exponentially stable. Moreover, the theoretical findings of this paper on the almost periodic solution are applied to prove the existence and stability of periodic solution for memristor-based shunting inhibitory cellular neural networks with leakage delays and periodic coefficients. An example is given to illustrate the effectiveness of the theoretical results. The results obtained in this paper are completely new and complement the previously known studies of Wu (2011) and Chen and Cao (2002).
format Online
Article
Text
id pubmed-5090130
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Hindawi Publishing Corporation
record_format MEDLINE/PubMed
spelling pubmed-50901302016-11-13 Almost Periodic Dynamics for Memristor-Based Shunting Inhibitory Cellular Neural Networks with Leakage Delays Lu, Lin Li, Chaoling Comput Intell Neurosci Research Article We investigate a class of memristor-based shunting inhibitory cellular neural networks with leakage delays. By applying a new Lyapunov function method, we prove that the neural network which has a unique almost periodic solution is globally exponentially stable. Moreover, the theoretical findings of this paper on the almost periodic solution are applied to prove the existence and stability of periodic solution for memristor-based shunting inhibitory cellular neural networks with leakage delays and periodic coefficients. An example is given to illustrate the effectiveness of the theoretical results. The results obtained in this paper are completely new and complement the previously known studies of Wu (2011) and Chen and Cao (2002). Hindawi Publishing Corporation 2016 2016-10-19 /pmc/articles/PMC5090130/ /pubmed/27840634 http://dx.doi.org/10.1155/2016/3587271 Text en Copyright © 2016 L. Lu and C. Li. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Lu, Lin
Li, Chaoling
Almost Periodic Dynamics for Memristor-Based Shunting Inhibitory Cellular Neural Networks with Leakage Delays
title Almost Periodic Dynamics for Memristor-Based Shunting Inhibitory Cellular Neural Networks with Leakage Delays
title_full Almost Periodic Dynamics for Memristor-Based Shunting Inhibitory Cellular Neural Networks with Leakage Delays
title_fullStr Almost Periodic Dynamics for Memristor-Based Shunting Inhibitory Cellular Neural Networks with Leakage Delays
title_full_unstemmed Almost Periodic Dynamics for Memristor-Based Shunting Inhibitory Cellular Neural Networks with Leakage Delays
title_short Almost Periodic Dynamics for Memristor-Based Shunting Inhibitory Cellular Neural Networks with Leakage Delays
title_sort almost periodic dynamics for memristor-based shunting inhibitory cellular neural networks with leakage delays
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5090130/
https://www.ncbi.nlm.nih.gov/pubmed/27840634
http://dx.doi.org/10.1155/2016/3587271
work_keys_str_mv AT lulin almostperiodicdynamicsformemristorbasedshuntinginhibitorycellularneuralnetworkswithleakagedelays
AT lichaoling almostperiodicdynamicsformemristorbasedshuntinginhibitorycellularneuralnetworkswithleakagedelays