subspace analysis
Face Recognition using Two dimensional Subspace Analysis and PNN
... In this paper, we present an new approach to face recognition based on the combination of feature extraction methods, such as two-dimensional DWT-2DPCA and DWT-2DLDA, with a probabilistic neural networks. This later is ...
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A web-based interactive data visualization system for outlier subspace analysis
... outlier subspace analysis in that the features and interface tools are special designed for effectively supporting human to observe and explore large volume high-dimensional data for gaining insight on ...
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The Stationary Subspace Analysis Toolbox
... The Stationary Subspace Analysis (SSA) algorithm linearly factorizes a high-dimensional time se- ries into stationary and non-stationary components. The SSA Toolbox is a platform-independent efficient ...
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Subspace Analysis of Indoor UWB Channels
... only subspace. L is the number of significant eigenvalues which also represents the channel DoFs [15], in the sense that any set of observations can be characterized by a set of approximately L independent random ...
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A web-based interactive data visualization system for outlier subspace analysis
... 19th International Conference on Software Engineering and Data Engineering SEDE-2010 SPONSOR International Society for Computers and Their Applications ISCA In cooperation with Winona St[r] ...
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Undercomplete Blind Subspace Deconvolution
... undercomplete version (uBSSD) of the task has been presented, and it has been shown how to derive an independent subspace analysis (ISA) task from the uBSSD problem. Recent developments of the ISA ...
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People identification and tracking through fusion of facial and gait features
... as subspace analysis [55] or sparse representation [82], and 2) blur-tolerant descriptor based meth- ods which attempt to extract blur insensitive features such as Local Phase Quantization (LPQ) ...
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An Efficient Approach for 3D Face Recognition Using ANN Based Classifiers
... comparative analysis of the neural network based classification algorithms has been put ...regression subspace analysis method of Face recognition ...two subspace analysis methods (PCA ...
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Human gait recognition with matrix representation
... coupled subspace analysis (CSA), is employed as a preprocessing step to remove noise and retain the most rep- resentative ...discriminant analysis with tensor representation, is applied to further ...
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Multiple Independent Subspace Clusterings
... independent subspace analysis to seek multiple and statistical independent ...each subspace, MISC per- forms graph regularized semi-nonnegative matrix factoriza- tion to explore ...
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Multi Dimension Support Vector Machine Based Crowd Detection and Localisation Framework for Varying Video Sequences
... adopted subspace evolution strate- gy for reconstructing the image of the object by constructing an update ...with subspace evolution strategy to track and detect the moving objects in the crowded scene ...
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Multidimensional entanglement transport through single-mode fiber
... count rates for distinguishing and erasing the OAM, in the ℓ = ±1 subspace, of photon B upon transmitting photon A through (A) free space and through (B) 250-m SMF. OAM (path) information is introduced into the ...
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Face recognition and verification using photometric stereo: The photoface database and a comprehensive evaluation
... unsupervised subspace methods (such as NMF, PCA, LDA etc) and Elastic Bunch Graph using jets using all four images with and without illumination compensation ([?], [?], [?]) and fuse the results (with weighted and ...
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Doppler Correction for Spatial Subspace Technique
... In this paper, a new ESPRIT method is developed based on the concept of subspace. Firstly, T-ESPRIT method algorithm is used to estimate DOA for each sub-array realizing time subspace concept. Secondly, ...
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Racial Disparity in Social Spatiality: Usage of National Parks and Opera Attendance
... closed subspace in C n [ 0 , 1 ] ...dimensional subspace of a normed vector space is ...proper subspace X of a normed vector space Y, at each point X p ∈ and for any ε > 0 , the ε -open ball is B ...
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Formulation of Finite Element Method for 1D and 2D Poisson Equation
... In our problem, we will have 13 nodes in the triangle, which is our domain. So we will have 13 trial or basis functions. We will also choose our test functions to be the same as the trial functions. Also we are working ...
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Krylov Subspace Solvers and Preconditioners
... Krylov subspace method can only be used if the coefficient matrix is symmetric and positive ...Krylov subspace methods for an increasing class of ...
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Subspace Learning with Partial Information
... · log(d) (see Theorem 7) on the sample complexity. We note that if is small enough, then the right term in the bound becomes irrelevant, and thus a linear dependence on d/r is obtained (for a detailed comparison, see ...
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Noisy Sparse Subspace Clustering
... Note that the LASSO Subspace Detection Property is a strong condition. In practice, spectral clustering does not require the exact block diagonal structure for perfect segmen- tation (check Figure 8b in our ...
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Angle of arrival estimation for broadband signals : a comparison
... signal subspace approach [2,4], covariance matrices are calculated in a number of frequency bins, which are then coherently combined such that their signal subspaces align into one single scalar-valued correlation ...
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