博碩士論文 100523019 完整後設資料紀錄

DC 欄位 語言
DC.contributor通訊工程學系zh_TW
DC.creator陳俊諺zh_TW
DC.creatorJiunn-Yann Chenen_US
dc.date.accessioned2013-7-2T07:39:07Z
dc.date.available2013-7-2T07:39:07Z
dc.date.issued2013
dc.identifier.urihttp://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=100523019
dc.contributor.department通訊工程學系zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract在本篇論文中,我們提出了一個適用於並行調適性濾波器的實數對稱限制最大事後機率演算法(CMA+RSC-MAP),首先將先介紹如何去推導出這個在盲目演算法中最大事後機率演算法具有的共軛對稱限制的最佳權重解,接下來我們利用這個共軛對稱限制的最佳權重解去導出這篇論文所提出的演算法,並且利用調適的方式讓權重能夠趨近於這個最佳權重解。最後在模擬的結果中,我們也會呈現出CMA+RSC-MAP演算法確實擁有比目前新型的並行調適性濾波器還要更好的效能。與原本的CMA+SC-MAP演算法相比,CMA+RSC-MAP演算法確實擁有跟CMA+SC-MAP演算法一樣好的效能,並且擁有更低的運算複雜度。zh_TW
dc.description.abstractIn this paper, we propose a real-valued SC-MAP (RSC-MAP) algorithm for concurrent adaptive filter (CAF) applied to beamforming. We first contribute to deriving a closed-form optimal weight expression for blind MAP algorithm. A conjugate symmetric property associated with optimal blind MAP weights is further acquired. Then, we use the conjugate symmetric constraint to guide the proposed RSC-MAP algorithms to follow the optimal blind MAP expression form during adapting procedure. In the simulations, we show that the proposed RSC-MAP algorithms have better performance than the classic ones. Compared with SC-MAP, the RSC-MAP with less computational complexity has the same bit-error rate performance.en_US
DC.subject最大事後機率zh_TW
DC.subject恆模數演算法zh_TW
DC.subject波束形成企zh_TW
DC.subject濾波器zh_TW
DC.subjectMaximum-a-posteriori probability estimationen_US
DC.subjectconstant modulus algorithmen_US
DC.subjectbeamformingen_US
DC.subjectfilteringen_US
DC.title適用於盲目的調適性波束形成器之低複雜度對稱限制最大事後機率演算法zh_TW
dc.language.isozh-TWzh-TW
DC.titleLow-Complexity Symmetry-Constrained Maximum-A-Posteriori Probability Algorithm for Adaptive Blind Beamformingen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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