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dc.contributor.author陳賢修en_US
dc.contributor.authorChen Shyan Shiouen_US
dc.contributor.author石至文en_US
dc.contributor.authorShih Chih Wenen_US
dc.date.accessioned2014-12-12T02:29:04Z-
dc.date.available2014-12-12T02:29:04Z-
dc.date.issued2001en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#NT900507003en_US
dc.identifier.urihttp://hdl.handle.net/11536/69297-
dc.description.abstract這篇論文分成三個部份。第一個部份研究 Transiently Chaotic Neural Network (TCNN) 系統中 Transversal Homoclinic Orbit 的存在性。第二個部份利用 Lyapunov function 來研究 TCNN 的穩定性。最後一個是研究 Discrete-Time Cellular Neural Networks (DT-CNN) 的混沌現象和穩定行為。這些定性的分析與研究有助於了解各別系統可能發生的行為。zh_TW
dc.description.abstractMy dissertation contains three parts. The subtitle of Part I is ``Transversal Homoclinic Orbits in a Transiently Chaotic Neural Network". Transiently chaotic neural network (TCNN) was proposed by Chen and Aihara~\cite{Aihara&Chen1995Chaotic}. We prove the existence of snap-back repellers in some parameters for TCNN. And, we generalize the result on the existence of a Lyapunov function for TCNN with the constant self-feedback connection weight from symmetric connection weights to cycle-symmetric ones. The Part II is entitled ``Asymptotic Behaviors in a Transiently Chaotic Neural Network". We prove an extended version of LaSalle's invariance principle for non-autonomous difference equations. Then, we apply the LaSalle's invariance principle to TCNN with cycle symmetric connection. The subtitle of Part III is ``Dynamics for Discrete-Time Cellular Neural Networks".en_US
dc.language.isoen_USen_US
dc.subject類神經網路zh_TW
dc.subject猛然回來的不隱定點zh_TW
dc.subject橫過的自連軌跡zh_TW
dc.subjectneural networken_US
dc.subjectsnap-back repelleren_US
dc.subjecttransversal homoclinic orbiten_US
dc.title離 散 型 神 經 網 路 的 動 態 行 為zh_TW
dc.titleDynamics in Discrete-Time Neural Networksen_US
dc.typeThesisen_US
dc.contributor.department應用數學系所zh_TW
顯示於類別:畢業論文