Best approximation and the Grassmann Matrix
Optimization algorithms on the Grassmann manifold with application to matrix eigenvalue problems
... the Grassmann manifold is shown to be expressed as a Lyapunov equation, and can be solved by applying an existing ...symmetric matrix characteristic of the Rayleigh quotient cost function has a degenerate ...
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A Grassmann Matrix Approach for the Computation of Degenerate Solutions for Output Feedback Laws
... the Grassmann variety of P ...the Grassmann Matrices and the first order conditions for optimality are reduced to a nonlinear eigenvalue-eigenvector ...
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Best Approximation in TVS
... In this paper we give new results on the best approxi- mation in the Hausdorff topological vector space and consider rela- tionship with orthogonality.. Introduction and Prelimiaries.[r] ...
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ON THE BEST APPROXIMATION OF THE DIFFERENTIATION OPERATOR
... the best approximation in the uniform norm of the differentiation operator of order k by bounded linear operators in the class of functions with the property that the Fourier transforms of their derivatives ...
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Best L1-approximation with splines
... discussed best L 1 -approximation for both the continu- ous case and the discrete ...the best L 1 -approximation in the continuous ...the best L 1 ...1 approximation that is ...
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Best Approximation and Moduli of Smoothness
... BEST APPROXIMATION AND MODULI OF SMOOTHNESS Teodora Dimova Zapryanova Dedicated to the 65 years Aniversary of Professor Petar Popivanov ...of approximation for characterization of the best ...
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Continuous Matrix Approximation on Distributed Data
... |kAxk 2 − kBxk 2 | ≤ εkAk 2 F for any unit vector x. Given the above connection, in this paper, first we pro- pose four novel methods for tracking weighted heavy hitters in a distributed stream of items (note that ...
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Sumit Chandok and T. D. Narang INVARIANT POINTS OF BEST APPROXIMATION AND BEST SIMULTANEOUS APPROXIMATION
... of best ap- proximation to the set of best simultaneous approximation, which is not necessarily ...on best approximation are ...
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1.Best approximation of functions of generalized Zygmund class by matrix-Euler summability means of Fourier series
... Best approximation, Fourier series, ( E, 1) means, matrix summability means and (∆ .E1 )- summability means, generalized Minkowski’s inequality, generalized Zygmund class.. 2013 Universi[r] ...
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Towards More Efficient SPSD Matrix Approximation and CUR Matrix Decomposition
... (SPSD) matrix approximation methods have been extensively used to speed up large-scale eigenvalue computation and kernel learning ...SPSD matrix approximation ...the matrix size n to ...
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Best Approximation in Uniformity Type Spaces
... University of Jordan, Department of mathematics, Amman-Jordan Abstract. Let X be a set, and Γ be a collection of subsets of X × X . The object of this paper, is to define a semi-linear uniform space by assuming certain ...
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Extensions of best approximation and coincidence theorems
... On the other hand, recently there have appeared some best approximation or fixed point theorems for maps whose domains and ranges have different topologies for example, see [9-17].. More[r] ...
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APPROXIMATION TO THE COVARIANCE MATRIX FOR STOCHASTIC POINT KINETICS
... precursors, time steps, Brownian motion and initial conditions. The results obtained by the numerical experiments are compared on mean with the deterministic model (DM) of the point kinetics which is calculated by the ...
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Lower bounds for the low rank matrix approximation
... low-rank matrix approximation ...low-rank matrix approximation ...low-rank approximation, when a perturbation E exists, there is an approximation error which cannot be avoided, ...
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Generalized Reich-Moore R-matrix approximation
... GRMA matrix elements Empirical fitting of Reich-Moore capture widths to neutron capture and cross section data using conventional Reich-Moore approximation often reveals variations among RMA capture ...
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Algorithms for the Rational Approximation of Matrix-Valued Functions
... of matrix-valued inter- ...with matrix-valued ...Loewner matrix), and to somehow restrict the search for the next interpolation point to a smaller ...
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Fast Approximation of Matrix Coherence and Statistical Leverage
... tall matrix,” and they concluded that their empir- ical results “suggest that random projection algorithms should be incorporated into future versions of L APACK ” (Avron et ...
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LLORMA: Local Low-Rank Matrix Approximation
... probabilistic matrix factorization (PMF) and later Salakhutdinov and Mnih (2008b) extended matrix factorization to fully Bayesian ap- ...in matrix completion were demonstrated in Toh and Yun (2010); ...
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Grassmann Learning for Recognition and Classification
... The Grassmann based algorithms are much better at classifying actions and recognizing faces than the non-Grassmann algorithms, with GRASP and GSR performing at or near the top for the single and all ...All ...
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Best approximation of functions in generalized Hölder class
... Several results on the error estimation of a function g in Lipschitz and Hölder classes by a trigonometric polynomial using different single and product means have been obtained by the researchers like [1–11], and [12]. ...
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