Anti-periodic solutions for high-order Hopfield neural networks with impulses
- Author
- QI WANG1 ; YAYUN FANG1 ; HUI LI1 ; LIJUAN SU1 ; BINXIANG DAI2
[1] School of Mathematical Sciences, Anhui University, Hefei 230601, China
[2] School of Mathematical Sciences and Computing Technology, Central South University, Changsha 410075, China - Source
Neurocomputing (Amsterdam). 2014, Vol 138, pp 339-346, 8 p ; ref : 40 ref
- ISSN
- 0925-2312
- Scientific domain
- Cognition; Computer science
- Publisher
- Elsevier, Amsterdam
- Publication country
- Netherlands
- Document type
- Article
- Language
- English
- Author keyword
- Anti-periodic solution Delays Existence and exponential stability High-order Hopfield neural networks Impulses
- Keyword (fr)
- Fonction Lyapunov Modèle Hopfield Modélisation Retard Réponse impulsion Réseau neuronal Solution périodique Stabilité exponentielle Système à retard Théorème point fixe
- Keyword (en)
- Lyapunov function Hopfield model Modeling Delay Pulse response Neural network Periodic solution Exponential stability Delay system Fixed point theorem
- Keyword (es)
- Función Lyapunov Modelo Hopfield Modelización Retraso Respuesta impulsión Red neuronal Solución periódica Estabilidad exponencial Sistema con retardo Teorema punto fijo
- Classification
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D02 Computer science; control theory; systems / 001D02C Artificial intelligence / 001D02C06 Connectionism. Neural networks
- Discipline
- Computer science : theoretical automation and systems
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 28469348
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
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DOI
10.1016/j.neucom.2014.01.028 
https://dx.doi.org/10.1016/j.neucom.2014.01.028
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