1. Açık Erişim@BUU
  2. İndeksli Yayınlar
  3. Web of Science
Please use this identifier to cite or link to this item: http://hdl.handle.net/11452/28381
Title: A novel condition for robust stability of delayed neural networks
Authors: Yücel, Eylem
Arık, Sabri
Uludağ Üniversitesi/Mühendislik Fakültesi/Elektrik-Elektronik Mühendisliği Bölümü.
Özcan, Neyir
7003726676
Keywords: Computer science
Lyapunov functional
Neural networks
Stability analysis
Asymptotic stability
Information science
Lyapunov functions
Robustness (control systems)
Stability
Delayed neural networks
Equilibrium point
Global robust asymptotic stabilities
Important features
Low computational complexity
Lyapunov functionals
Lyapunov stability theorem
Complex networks
Issue Date: 2015
Publisher: Springer
Citation: Neyir, Ö. vd. (2015). "A novel condition for robust stability of delayed neural networks". Neural Information Processing, PT III, Lecture Notes in Computer Science, 273-280.
Abstract: This paper presents a novel sufficient condition for the existence, uniqueness and global robust asymptotic stability of the equilibrium point for the class of delayed neural networks by using the Homomorphic mapping and the Lyapunov stability theorems. An important feature of the obtained result is its low computational complexity as the reported result can be verified by checking some well-known properties of some certain classes of matrices, which simplify the verification of the derived result.
Description: Bu çalışma, 9-12 Kasım 2015 tarihleri arasında İstanbul[Türkiye]'da düzenlenen 22. International Conference on Neural Information Processing (ICONIP)'de bildiri olarak sunulmuştur.
URI: https://doi.org/10.1007/978-3-319-26555-1_31
http://hdl.handle.net/11452/28381
ISBN: 978-3-319-26555-1
978-3-319-26554-4
ISSN: 0302-9743
Appears in Collections:Scopus
Web of Science

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