Symmetric positive definite matrix
Matrix Exponentiated Gradient Updates for On-line Learning and Bregman Projection
... a symmetric positive definite ...a symmetric positive definite matrix subject to linear ...a symmetric positive definite matrix of trace one ...
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Computing Centre Newsletter No. 22, June 1978
... INVERSION OF MATRIX- POSITIVE DEFINITE- SYMMETRIC BAND MATRIX SYMMETRIC BAND STORAGE MODE SPACE ECONOMIZER SOLUTION.. PSEUDO INVERSE OF A MATRIX..[r] ...
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Unconditionally stable scheme for Riccati equation
... • We observe that the differential system (1) (6) together with the initial condition (2) and the final condition (7) is coupled through the optimality condition (8). In practice, we need a linear feedback function of ...
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Learning the Kernel Matrix with Semidefinite Programming
... kernel matrix is an important topic for further ...Gram matrix “experts”—it is also worth considering other parameterizations as ...kernel matrix is convex with respect to the parameters of the ...
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The Role of Riemannian Manifolds in Computer Vision: From Coding to Deep Metric Learning
... Making use of structured descriptors has been shown to be effective in a wide range of com- puter vision tasks. A notable example is the Diffusion Tensor Imaging (DTI) technique which represents each voxel in 3-D brain ...
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A Particular Matrix, Its Inversion and Some Norms
... In this paper we investigated some properties of a new special matrix. We found remarkable relations about this matrix. We saw that this matix is positive definite and has a tridiagonal ...
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Sum of squared logarithms an inequality relating positive definite matrices and their matrix logarithm
... The structure of the inequality in dimensions n = and n = and extensive numerical sampling strongly suggest that the inequality holds for all n ∈ N if the n corresponding conditions are satisfied. More precisely, in ...
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4826.pdf
... Symmetric positive-definite (SPD) matrix-valued data occur in many applications. This has motivated the recent development of several methods for statistical analysis of SPD matrices as ...
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Finite difference methods for computing eigenvalues of fourth order boundary value problems
... Central difference formula, Finite difference methods, Generalized symmetric eigenvalue problem, Positive definite matrix, Two-point boundary value problem.. INTRODUCT ION We shall consi[r] ...
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Threshold Extension of Gallium Arsenide/Aluminum Gallium Arsenide Terahertz Detectors and Switching in Heterostructures
... real, symmetric matrices is an inner product space with < A, B >= ...a matrix P is positive semidefinite if and only if tr(P Q) ≥ 0 for every Q ≥ ...is positive definite if and ...
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A coarse space for heterogeneous Helmholtz problems based on the Dirichlet-to-Neumann operator
... For symmetric positive definite (spd) matrices, this question has been examined extensively ...preconditioned matrix worse for any choice of Z [40, Theorem ...
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Symmetric and Positive Definite Broyden Update for Unconstrained Optimization
... Remark: the mean of Nan is ∞ ∞ or 0. ∞ or 0 0 . From Table (1), it’s clear that SPBR1 has a performance better than Broyden update, and we can note that the Broyden update cannot solve problem 3 at all starting points ...
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Integrals of Four Variables with Statistical Distribution associated with hyper geometric Function of Matrix Argument
... of matrix argument with their statistical ...real positive definite symmetric of order m x ...introducing matrix sequences, matrix series, and concepts analogous to convergence ...
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Low Rank Positive Approximants of Symmetric Matrices
... in positive approximants was initiated in Halmos’ paper [4], which considers the solution of ...the positive approximant problem in a more general context of linear operators on a Hilbert ...Other ...
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Computing the Matrix Geometric Mean of Two HPD Matrices: A Stable Iterative Method
... As pointed out by some practitioners, see e.g. [1] and the references cited therein, one efficient way to design new iterative methods for some ma- trix functions is to apply the zero-finding itera- tive methods for ...
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Selberg-type squared matrices gamma and beta integrals
... a positive signature symmetric matrix Selberg-type gamma ...The positive signature symmetric matrice Selberg-type beta integrals follow on the same ...skew symmetric matrices ...
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Positive Definite Matrix Space Based Detector with Limited Training Samples for Multiple Target Situations
... covariance matrix C is made of a length N of reference window, namely C = ¯ X X ¯ T ...covariance matrix C is 0, and its rank (R) is 1, which make it a singular ...be positive-definite, optimization ...
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New Model for L2 Norm Flow
... the matrix geometry such that the L 2 norm is ...initial matrix is a positive ...initial matrix and the flow converges the scalar matrix with the same trace as the initial ...
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Refinements of Results about Weighted Mixed Symmetric Means and Related Cauchy Means
... A recent refinement of the classical discrete Jensen inequality is given by Horv´ath and Peˇcari´c. In this paper, the corresponding weighted mixed symmetric means and Cauchy-type means are defined. We investigate ...
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On generating correlated random variables with a given valid or invalid Correlation matrix
... be done by some text editor such as EDIT.COM (a DOS program of MICROSOFT). The name of this file is, say inputfile. When the program runs, it asks for the value of m (order of the matrix) and the inputfile name ...
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