A NEW CRITERION FOR STABILITY OF NEUTRAL-TYPE HOPFIELD NEURAL NETWORKS WITH CONSTANT DELAYS

This paper makes some contributions to the stability problem of neutral-type Hopfield neural network model having a constant time delay in states of neurons and a constant neutral delay in the time derivatives of states of neurons. With the help of a suitable Lyapunov functional, a novel stability c...

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Main Author: Özlem Faydasıçok
Format: Article
Language:English
Published: Bursa Uludag University 2020-08-01
Series:Uludağ University Journal of The Faculty of Engineering
Subjects:
Online Access:https://dergipark.org.tr/tr/pub/uumfd/issue/55761/716884
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author Özlem Faydasıçok
author_facet Özlem Faydasıçok
author_sort Özlem Faydasıçok
collection DOAJ
description This paper makes some contributions to the stability problem of neutral-type Hopfield neural network model having a constant time delay in states of neurons and a constant neutral delay in the time derivatives of states of neurons. With the help of a suitable Lyapunov functional, a novel stability criterion is derived for neutral-type Hopfield neural network model. This stability criterion only requires to check the positive defineteness of the matrices involving the system elements of this type of neural networks. The presented stability condition proved to be independently of these time and neutral delays. Therefore, this condition can be easily justified by applying the properties of some certain matrices. A numerical example for this type of neutral systems is studied to show the applicability of the presented stability result.
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spelling doaj.art-829c748ccdf549ebb2f6e156ca3a4dd12023-02-15T16:21:41ZengBursa Uludag UniversityUludağ University Journal of The Faculty of Engineering2148-41472148-41552020-08-0125263965010.17482/uumfd.7168841779A NEW CRITERION FOR STABILITY OF NEUTRAL-TYPE HOPFIELD NEURAL NETWORKS WITH CONSTANT DELAYSÖzlem Faydasıçok0İstanbul ÜniversitesiThis paper makes some contributions to the stability problem of neutral-type Hopfield neural network model having a constant time delay in states of neurons and a constant neutral delay in the time derivatives of states of neurons. With the help of a suitable Lyapunov functional, a novel stability criterion is derived for neutral-type Hopfield neural network model. This stability criterion only requires to check the positive defineteness of the matrices involving the system elements of this type of neural networks. The presented stability condition proved to be independently of these time and neutral delays. Therefore, this condition can be easily justified by applying the properties of some certain matrices. A numerical example for this type of neutral systems is studied to show the applicability of the presented stability result.https://dergipark.org.tr/tr/pub/uumfd/issue/55761/716884nötral-tip sistemlerhopfield sinir ağlarılyapunov fonksiyonellerikararlılık analizineutral-type systemshopfield neural networkslyapunov functionalsstability analysis
spellingShingle Özlem Faydasıçok
A NEW CRITERION FOR STABILITY OF NEUTRAL-TYPE HOPFIELD NEURAL NETWORKS WITH CONSTANT DELAYS
Uludağ University Journal of The Faculty of Engineering
nötral-tip sistemler
hopfield sinir ağları
lyapunov fonksiyonelleri
kararlılık analizi
neutral-type systems
hopfield neural networks
lyapunov functionals
stability analysis
title A NEW CRITERION FOR STABILITY OF NEUTRAL-TYPE HOPFIELD NEURAL NETWORKS WITH CONSTANT DELAYS
title_full A NEW CRITERION FOR STABILITY OF NEUTRAL-TYPE HOPFIELD NEURAL NETWORKS WITH CONSTANT DELAYS
title_fullStr A NEW CRITERION FOR STABILITY OF NEUTRAL-TYPE HOPFIELD NEURAL NETWORKS WITH CONSTANT DELAYS
title_full_unstemmed A NEW CRITERION FOR STABILITY OF NEUTRAL-TYPE HOPFIELD NEURAL NETWORKS WITH CONSTANT DELAYS
title_short A NEW CRITERION FOR STABILITY OF NEUTRAL-TYPE HOPFIELD NEURAL NETWORKS WITH CONSTANT DELAYS
title_sort new criterion for stability of neutral type hopfield neural networks with constant delays
topic nötral-tip sistemler
hopfield sinir ağları
lyapunov fonksiyonelleri
kararlılık analizi
neutral-type systems
hopfield neural networks
lyapunov functionals
stability analysis
url https://dergipark.org.tr/tr/pub/uumfd/issue/55761/716884
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