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Titlebook: Matrix Information Geometry; Frank Nielsen,Rajendra Bhatia Book 2013 Springer-Verlag Berlin Heidelberg 2013 Audio Signal Processing.Covari

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書目名稱Matrix Information Geometry
編輯Frank Nielsen,Rajendra Bhatia
視頻videohttp://file.papertrans.cn/628/627752/627752.mp4
概述Presents advances in matrix and tensor data processing in the domain of signal, image and information processing.Written by experts in the areas of theoretical mathematics or engineering sciences.Disc
圖書封面Titlebook: Matrix Information Geometry;  Frank Nielsen,Rajendra Bhatia Book 2013 Springer-Verlag Berlin Heidelberg 2013 Audio Signal Processing.Covari
描述This book presents advances in matrix and tensor data processing in the domain of signal, image and information processing. The theoretical mathematical approaches are discusses in the context of potential applications in sensor and cognitive systems engineering. .The topics and application include Information Geometry, Differential Geometry of structured Matrix, Positive Definite Matrix, Covariance Matrix, Sensors (Electromagnetic Fields, Acoustic sensors) and? Applications in Cognitive systems, in particular Data Mining.
出版日期Book 2013
關(guān)鍵詞Audio Signal Processing; Covariance matrix; Differential geometry of structured matrix; Fixed-Point SVD
版次1
doihttps://doi.org/10.1007/978-3-642-30232-9
isbn_softcover978-3-642-44847-8
isbn_ebook978-3-642-30232-9
copyrightSpringer-Verlag Berlin Heidelberg 2013
The information of publication is updating

書目名稱Matrix Information Geometry影響因子(影響力)




書目名稱Matrix Information Geometry影響因子(影響力)學(xué)科排名




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書目名稱Matrix Information Geometry網(wǎng)絡(luò)公開度學(xué)科排名




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書目名稱Matrix Information Geometry年度引用學(xué)科排名




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書目名稱Matrix Information Geometry讀者反饋學(xué)科排名




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The Riemannian Mean of Positive Matricesf intrinsic connections with Riemannian geometry. This mean has also been adopted for applications in image processing, elasticity and other areas. This article is a broad survey of this topic and also reports on some very recent work that is yet to appear in print.
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Doppler Information Geometry for Wake Turbulence Monitoringnce matrices of order . as a manifold .. Geometries of covariance matrices based on two kinds of radar data models are presented. Finally, a radar detector based on Doppler entropy assessment is analyzed and applied for wake turbulence monitoring. This advanced Doppler processing chain is also implemented by CUDA codes for GPU parallel computation
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