Stability and Synchronization Control of Stochastic Neural Networks [recurso electrónico] / by Wuneng Zhou, Jun Yang, Liuwei Zhou, Dongbing Tong.

Por: Zhou, Wuneng [author.]Colaborador(es): Yang, Jun [author.] | Zhou, Liuwei [author.] | Tong, Dongbing [author.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries Studies in Systems, Decision and Control ; 35Editor: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2016Edición: 1st ed. 2016Descripción: XVI, 357 p. 82 illus., 80 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783662478332Tema(s): Engineering | Neural networks (Computer science) | Computational intelligence | Control engineering | Engineering | Control | Mathematical Models of Cognitive Processes and Neural Networks | Computational IntelligenceFormatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD: 629.8 Clasificación LoC:TJ212-225Recursos en línea: Libro electrónicoTexto
Contenidos:
Relative Mathematic Foundation -- Asymptotical and Exponential Stability and Synchronization for NN -- Robust Stability and Synchronization for NN -- Adaptive Stability and Synchronization for NN -- Stability and Synchronization for Neutral-type NN -- Stability and Synchronization for NN with Levy Noise -- Some Applications to Finance Based-on NN.
En: Springer eBooksResumen: This book reports on the latest findings in the study of Stochastic Neural Networks (SNN). The book collects the novel model of the disturbance driven by Levy process, the research method of M-matrix, and the adaptive control method of the SNN in the context of stability and synchronization control. The book will be of interest to university researchers, graduate students in control science and engineering and neural networks who wish to learn the core principles, methods, algorithms and applications of SNN.
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Relative Mathematic Foundation -- Asymptotical and Exponential Stability and Synchronization for NN -- Robust Stability and Synchronization for NN -- Adaptive Stability and Synchronization for NN -- Stability and Synchronization for Neutral-type NN -- Stability and Synchronization for NN with Levy Noise -- Some Applications to Finance Based-on NN.

This book reports on the latest findings in the study of Stochastic Neural Networks (SNN). The book collects the novel model of the disturbance driven by Levy process, the research method of M-matrix, and the adaptive control method of the SNN in the context of stability and synchronization control. The book will be of interest to university researchers, graduate students in control science and engineering and neural networks who wish to learn the core principles, methods, algorithms and applications of SNN.

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