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Analysis and control of coupled neur...

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Analysis and control of coupled neural networks with reaction-diffusion terms

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Analysis and control of coupled neural networks with reaction-diffusion termsby Jin-Liang Wang ... [et al.].
其他作者:	Wang, Jin-Liang.
出版者:	Singapore :Springer Singapore :2018.
面頁冊數:	xiii, 220 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
標題:	Neural networks (Computer science)
電子資源:	http://dx.doi.org/10.1007/978-981-10-4907-1
ISBN:	9789811049071$q(electronic bk.)

Analysis and control of coupled neural networks with reaction-diffusion terms
Analysis and control of coupled neural networks with reaction-diffusion terms[electronic resource] /by Jin-Liang Wang ... [et al.]. - Singapore :Springer Singapore :2018. - xiii, 220 p. :ill. (some col.), digital ;24 cm.

Introduction -- Pinning control strategies for synchronization of Coupled Reaction-Diffusion Neural Networks -- Pinning control for synchronization of Coupled Reaction-Diffusion Neural Networks with directed topologies -- Impulsive control for the synchronization of Coupled Reaction-Diffusion Neural Networks -- Novel adaptive strategies for synchronization of Coupled Reaction-Diffusion Neural Networks -- Synchronization and adaptive control of Coupled Reaction-Diffusion Neural Networks with hybrid coupling -- Passivity-based synchronization of Coupled Reaction-Diffusion Neural Networks with time-varying delay -- Passivity and synchronization of Coupled Reaction-Diffusion Neural Networks with adaptive coupling -- Passivity analysis of Coupled Reaction-Diffusion Neural Networks with Dirichlet boundary conditions -- Passivity of directed and undirected Coupled Reaction-Diffusion Neural Networks with adaptive coupling weights.

This book introduces selected recent findings on the analysis and control of dynamical behaviors for coupled reaction-diffusion neural networks. It presents novel research ideas and essential definitions concerning coupled reaction-diffusion neural networks, such as passivity, adaptive coupling, spatial diffusion coupling, and the relationship between synchronization and output strict passivity. Further, it gathers research results previously published in many flagship journals, presenting them in a unified form. As such, the book will be of interest to all university researchers and graduate students in Engineering and Mathematics who wish to study the dynamical behaviors of coupled reaction-diffusion neural networks.

ISBN: 9789811049071$q(electronic bk.)

Standard No.: 10.1007/978-981-10-4907-1doiSubjects--Topical Terms:

181982
Neural networks (Computer science)

LC Class. No.: QA76.87

Dewey Class. No.: 006.32

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505 0 $a Introduction -- Pinning control strategies for synchronization of Coupled Reaction-Diffusion Neural Networks -- Pinning control for synchronization of Coupled Reaction-Diffusion Neural Networks with directed topologies -- Impulsive control for the synchronization of Coupled Reaction-Diffusion Neural Networks -- Novel adaptive strategies for synchronization of Coupled Reaction-Diffusion Neural Networks -- Synchronization and adaptive control of Coupled Reaction-Diffusion Neural Networks with hybrid coupling -- Passivity-based synchronization of Coupled Reaction-Diffusion Neural Networks with time-varying delay -- Passivity and synchronization of Coupled Reaction-Diffusion Neural Networks with adaptive coupling -- Passivity analysis of Coupled Reaction-Diffusion Neural Networks with Dirichlet boundary conditions -- Passivity of directed and undirected Coupled Reaction-Diffusion Neural Networks with adaptive coupling weights.
520 $a This book introduces selected recent findings on the analysis and control of dynamical behaviors for coupled reaction-diffusion neural networks. It presents novel research ideas and essential definitions concerning coupled reaction-diffusion neural networks, such as passivity, adaptive coupling, spatial diffusion coupling, and the relationship between synchronization and output strict passivity. Further, it gathers research results previously published in many flagship journals, presenting them in a unified form. As such, the book will be of interest to all university researchers and graduate students in Engineering and Mathematics who wish to study the dynamical behaviors of coupled reaction-diffusion neural networks.
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