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Cognitive Neurodynamics
Erschienen in: Cognitive Neurodynamics 4/2010

01.12.2010 | Research article

Robust stability analysis of delayed Takagi-Sugeno fuzzy Hopfield neural networks with discontinuous activation functions

verfasst von: Xiru Wu, Yaonan Wang, Lihong Huang, Yi Zuo

Erschienen in: Cognitive Neurodynamics | Ausgabe 4/2010

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Abstract

In this paper, the global robust stability problem of delayed Takagi–Sugeno fuzzy Hopfield neural networks with discontinuous activation functions (TSFHNNs) is considered. Based on Lyapunov stability theory and M-matrices theory, we derive a stability criterion to guarantee the global robust stability of TSFHNNs. Compared with the existing literature, we remove the assumptions on the neuron activations such as Lipschitz conditions, bounded, monotonic increasing property or the assumption that the right-limit value is bigger than the left one at the discontinuous point. Finally, two numerical examples are given to show the effectiveness of the proposed stability results.
Vorheriger Artikel Neural coding properties based on spike timing and pattern correlation of retinal ganglion cells
Nächster Artikel Generalized optimal spatial filtering using a kernel approach with application to EEG classification

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Metadaten
Titel
Robust stability analysis of delayed Takagi-Sugeno fuzzy Hopfield neural networks with discontinuous activation functions
verfasst von
Xiru Wu
Yaonan Wang
Lihong Huang
Yi Zuo
Publikationsdatum
01.12.2010
Verlag
Springer Netherlands
Erschienen in
Cognitive Neurodynamics / Ausgabe 4/2010
Print ISSN: 1871-4080
Elektronische ISSN: 1871-4099
DOI
https://doi.org/10.1007/s11571-010-9123-z

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