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Cognitive Neurodynamics
Erschienen in: Cognitive Neurodynamics 2/2011

01.06.2011 | Research Article

Design of delay-dependent state estimator for discrete-time recurrent neural networks with interval discrete and infinite-distributed time-varying delays

verfasst von: Chin-Wen Liao, Chien-Yu Lu

Erschienen in: Cognitive Neurodynamics | Ausgabe 2/2011

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Abstract

The state estimation problem for discrete-time recurrent neural networks with both interval discrete and infinite-distributed time-varying delays is studied in this paper, where interval discrete time-varying delay is in a given range. The activation functions are assumed to be globally Lipschitz continuous. A delay-dependent condition for the existence of state estimators is proposed based on new bounding techniques. Via solutions to certain linear matrix inequalities, general full-order state estimators are designed that ensure globally asymptotic stability. The significant feature is that no inequality is needed for seeking upper bounds for the inner product between two vectors, which can reduce the conservatism of the criterion by employing the new bounding techniques. Two illustrative examples are given to demonstrate the effectiveness and applicability of the proposed approach.
Vorheriger Artikel Generalization of learning by synchronous waves: from perceptual organization to invariant organization
Nächster Artikel Visualization for understanding of neurodynamical systems

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Metadaten
Titel
Design of delay-dependent state estimator for discrete-time recurrent neural networks with interval discrete and infinite-distributed time-varying delays
verfasst von
Chin-Wen Liao
Chien-Yu Lu
Publikationsdatum
01.06.2011
Verlag
Springer Netherlands
Erschienen in
Cognitive Neurodynamics / Ausgabe 2/2011
Print ISSN: 1871-4080
Elektronische ISSN: 1871-4099
DOI
https://doi.org/10.1007/s11571-010-9135-8

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