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dc.contributor.author殷蕾如en_US
dc.contributor.authorLei-Ju Yinen_US
dc.contributor.author石至文en_US
dc.contributor.authorChih-Wen Shihen_US
dc.date.accessioned2014-12-12T02:26:16Z-
dc.date.available2014-12-12T02:26:16Z-
dc.date.issued2000en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#NT890507013en_US
dc.identifier.urihttp://hdl.handle.net/11536/67693-
dc.description.abstract在這篇論文之中,我們探討具短暫混沌性質的一種神經網路。我們將其中之對稱連接推廣到循環對稱連接。我們將討論此神經網路關於Lyapunov函數及其固定點的終極穩定性。在討論中,我們同時考慮了此神經網路之同步更新及循環更新的形式。比較這兩種更新形式的神經網路動態是很值得探討的課題。zh_TW
dc.description.abstractThis investigation extends the existence of Lyapunov function and asymptotic stability of fixed points for transiently chaotic neural networks from symmetric connectivity to cycle-symmetric connectivity. Both synchronous updating mode and cyclic updating mode for the networks are considered. It is of interest to compare the respective dynamics of the networks corresponding to these two different modes.en_US
dc.language.isoen_USen_US
dc.subject神經網路zh_TW
dc.subjectCyclicen_US
dc.subjectNeural Netoworksen_US
dc.title循環更新形式之神經網路zh_TW
dc.titleCyclic-Updating in Neural Networksen_US
dc.typeThesisen_US
dc.contributor.department應用數學系所zh_TW
Appears in Collections:Thesis