Stabilité Exponentielle Globale des Réseaux de Neurones Récurrents Généralisés à Retards Discrets et Distribués
| dc.contributor.author | KECHAR, Youcef | |
| dc.contributor.author | Merabet, Brahim Encadreur | |
| dc.date.accessioned | 2025-09-14T08:29:42Z | |
| dc.date.available | 2025-09-14T08:29:42Z | |
| dc.date.issued | 2025 | |
| dc.description | Spécialité : Analyse Fonctionnelle et Applications | EN_en |
| dc.description.abstract | In this memoir, we deal with the problem of analyzing the global exponential stability of a class of recurrent neural networks (RNNs) with discrete and distributed mixed delays, let us consider the existence and uniqueness of équilibriste points. use a new Lyapunov-krasvsckii functional and develop a linear matrix inequality (LMI) approach to make RNNs exponentially global stable. | EN_en |
| dc.identifier.uri | https://dspace.univ-ghardaia.edu.dz/xmlui/handle/123456789/9790 | |
| dc.publisher | université Ghardaia | EN_en |
| dc.subject | :Generalized recurrent neural networks; Discrete and distributed delays; Lyapunov- Krasovskii functional; Global exponential stability; Global asymptotic stability. | EN_en |
| dc.subject | :Réseaux de neurones récurrents généralisés ; Retards discrets et distribués ;fonc- tionnelle Lyapunov-Krasovskii ; Stabilité exponentielle globale ; Stabilité asymptotique globale. | EN_en |
| dc.title | Stabilité Exponentielle Globale des Réseaux de Neurones Récurrents Généralisés à Retards Discrets et Distribués | EN_en |
| dc.type | Thesis | EN_en |
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