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Titlebook: Analysis and Control of Coupled Neural Networks with Reaction-Diffusion Terms; Jin-Liang Wang,Huai-Ning Wu,Shun-Yan Ren Book 2018 Springer

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樓主
發(fā)表于 2025-3-21 19:33:31 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Analysis and Control of Coupled Neural Networks with Reaction-Diffusion Terms
影響因子2023Jin-Liang Wang,Huai-Ning Wu,Shun-Yan Ren
視頻videohttp://file.papertrans.cn/157/156162/156162.mp4
發(fā)行地址Takes the reaction-diffusion effect into account in neural networks.Proposes new passivity definitions for cases in which the input and output vectors have different dimensions in coupled reaction-dif
圖書封面Titlebook: Analysis and Control of Coupled Neural Networks with Reaction-Diffusion Terms;  Jin-Liang Wang,Huai-Ning Wu,Shun-Yan Ren Book 2018 Springer
影響因子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..
Pindex Book 2018
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發(fā)表于 2025-3-21 22:43:47 | 只看該作者
Novel Adaptive Strategies for Synchronization of CRDNNs,is not only dependent on the time, but also intensively dependent on space variable in many circumstances. As a well-known example of complex networks, food webs attract increasing attention of researchers from different fields in recent years.
板凳
發(fā)表于 2025-3-22 00:26:19 | 只看該作者
Ehsaneddin Jalilian,Andreas Uhl and nonlinear functions approximation. These applications heavily depend on the dissipativity, stability, asymptotic stability, passivity, output strict passivity, and synchronization of neural networks.
地板
發(fā)表于 2025-3-22 05:48:40 | 只看該作者
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發(fā)表于 2025-3-22 15:10:56 | 只看該作者
Felix Juefei-Xu,Eshan Verma,Marios SavvidesIn many circumstances, complex dynamical networks can not be synchronized by themselves, thus some control strategies should be adopted to achieve synchronization.
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發(fā)表于 2025-3-22 19:57:32 | 只看該作者
Deep Learning for Tattoo RecognitionUp to date, many researchers have devoted much effort to synchronization problem for CNNs because of its wide applications in different fields.
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發(fā)表于 2025-3-23 07:16:06 | 只看該作者
Parabolic ,-systems: boundary regularity,Passivity is part of a broader and a general theory of dissipativeness [105, 183].
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