Treffer: Further results on robust stability of bidirectional associative memory neural networks with norm-bounded uncertainties
Title:
Further results on robust stability of bidirectional associative memory neural networks with norm-bounded uncertainties
Authors:
Source:
Neurocomputing (Amsterdam). 148:535-543
Publisher Information:
Amsterdam: Elsevier, 2015.
Publication Year:
2015
Physical Description:
print, 35 ref
Original Material:
INIST-CNRS
Subject Terms:
Cognition, Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Logiciel, Software, Systèmes informatiques et systèmes répartis. Interface utilisateur, Computer systems and distributed systems. User interface, Intelligence artificielle, Artificial intelligence, Connexionnisme. Réseaux neuronaux, Connectionism. Neural networks, Borne supérieure, Upper bound, Cota superior, Fonction Lyapunov, Lyapunov function, Función Lyapunov, Mémoire associative bidirectionnelle, Bidirectional associative memory, Memoria asociativa bidireccional, Mémoire associative, Associative memory, Memoria asociativa, Mémoire dynamique, Dynamical storage, Memoria dinámica, Méthode Lyapunov, Lyapunov method, Método Lyapunov, Réseau neuronal, Neural network, Red neuronal, Stabilité robuste, Robust stability, Estabilidad robusta, Hétéroassociation, Heteroassociation, heteroasociación, Bidirectional associative memory neural networks, Lyapunov functional, Norm-bounded uncertainties
Document Type:
Fachzeitschrift
Article
File Description:
text
Language:
English
Author Affiliations:
College of Automation, Chongqing University, 400030 Chongqing, China
Department of Mathematics and Information Engineering, Chongqing University of Education, 400065 Chongqing, China
School of Engineering, University of Guelph, Guelph, Ontairo N1G 2W1, Canada
Department of Mathematics and Information Engineering, Chongqing University of Education, 400065 Chongqing, China
School of Engineering, University of Guelph, Guelph, Ontairo N1G 2W1, Canada
ISSN:
0925-2312
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.28844566
Database:
PASCAL Archive
Weitere Informationen
In this paper, we have a further study about global robust stability of dynamical bidirectional associative memory (BAM) neural networks with norm-bounded uncertainties. By introducing four new upper bound norms for the interconnection matrices of the neural networks and constructing a suitable Lyapunov functional, several new criteria on global robust stability are established. The obtained results can be easily verified as they can be expressed in terms of the network parameters only. In comparison with the results reported in the literature, the proposed approach leads to results with less restrictive conditions. Two numerical examples are also worked through to illustrate our results.