Projection onto convex sets
Rapid Magnetic Resonance Imaging Using Undersampled Projection-Onto-Convex-Sets Reconstruction Mohammad Sabati* 1,2 , Leila Borvayeh 3
... Scan time reduction is important in clinical magnetic resonance imaging (MRI). Partial Fourier data acquisitions rely on the conjugate symmetry of Hermitian data, allowing for shorter scan times due to fewer ...
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Projection onto Convex Sets Method in Spacefrequency Domain for Super Resolution
... Abstract—The aim of super resolution is to get high resolution (HR) images/videos from low-resolution (LR) images/videos. The obtained HR images/videos are expected to be clear and have less artifacts. Projection ...
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Implementation of a projection onto convex sets iteration based image coder
... On the other hand, if the intersection is empty, the POCS method will find the closest image, described by the selected number of coefficients, to the image to be encoded considering onl[r] ...
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Super Resolution of an Image using Projection onto Convex Set Algorithm
... Yu,” Projection onto Convex Sets Super-resolution Image Reconstruction Based on Wavelet Bi-cubic Interpolation,” 2011 International Conference on Electronic & Mechanical Engineering and ...
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A simple algorithm for computing projection onto intersection of finite level sets
... this result for alternating projections between any finite collection of closed convex sets. Strong convergence also holds when the sets are symmetric [, Theorem .; , Corol- lary .]. However, ...
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Continuity properties of projection operators
... uniformly convex and uniformly ...the projection operator in a Hilbert space whereas the estimates of [32] (which rely on different techniques from [11, 37, 41]) enable one to recover this classical ...
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Functionally closed sets and functionally convex sets in real Banach spaces
... In this work, by defining two notions F -convexity and F -closedness of subsets of Banach spaces, we improve some basic theorems in functional analysis. The Krein-Milman theorem has been generalized on finite dimensional ...
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Strong convergence by a hybrid algorithm for solving generalized mixed equilibrium problems and fixed point problems of a Lipschitz pseudo-contraction in Hilbert spaces
... closed convex sets based on the hybrid shrinking projection methods to find a common solution of fixed point problems of a Lipschitz pseudo-contraction and generalized mixed equilibrium problems in ...
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On the Convex Feasibility Problem
... the projection algorithm for solving the convex feasibility problem for a family of closed convex sets, is in connection with the regularity properties of the ...closed convex ...
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Fitting Convex Sets to Data: Algorithms and Applications
... projections onto manifolds rather than on convex optimization, and the types of guarantees obtained in [151] are qualitatively quite different in comparison to ...a projection along the di- rection ...
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Computing Convex Coverage Sets for Faster Multi-objective Coordination
... A highly prevalent scenario is that, in addition to f being monotonically increasing, we also know that it is linear, that is, the parameter vectors w are weights by which the values of the individual objectives are ...
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Some fixed point theorems in locally p-convex spaces
... In nonlinear analysis, one of the dynamic research areas is investigation of existence of a fixed point of maps on convex sets and p-convex sets. Recently, a number of fixed point theorems have ...
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Introduction to Cartesian Geometry and Cartesianization of Complex Shapes
... the convex analysis, a branch that has had fertile tracks in analytical and even geometric ...that convex analysis and Cartesian analysis coincide in particular cases but generally they are ...are ...
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Regularized gradient projection methods for equilibrium and constrained convex minimization problems
... Theorem . Let C be a nonempty, closed and convex subset of a Hilbert space H. Let φ be a bifunction from C × C → R satisfying (A)-(A), and let f : C → R be a real-valued convex function, and assume that ...
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On mean curvature integrals of the outer parallel body of the projection of a convex body
... K in space forms and gave the expression of it in terms of M j (r) , where M (r) j is the jth mean curvature integral of K in r-dimensional geodesic submanifold, their work extends the re- sult of Santaló in []. In [], ...
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On hyperspaces of max-plus and max-min convex sets
... In the sequel, we will need the following notion, which was introduced in [11]: a c-structure on a topological space X is an assignment, to every nonempty finite subset A of X , of a contractible subspace F (A) of X, ...
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Reconstruction from limited projection data using fuzzy sets
... This necessitates the use of a reconstruction algorithm which incorporates all available a priori information about the reconstructed image and the projection process.. Recently, in many[r] ...
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Adaptive Projection Confidence Sets and Data Analyses in Personalized Medicine.
... confidence sets for θ ∗ (β ∗ ...the projection confidence interval (PCI), which was first proposed by Berger and Boos (1994), and later discussed by Robins ...
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Characterization of Best Approximants from Convex Subsets and Level Sets in Normed Linear Spaces
... Some new characterization of best approximants from convex sub- sets and level sets of convex mappings in normed linear spaces in terms of norm derivatives and sub-orthogonality in Birkh[r] ...
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The Projection of a Test Genome onto a Reference Population and Applications to Humans and Archaic Hominins
... of a Yoruba genome projected onto CEU and of a French genome projected onto YRI. The visual differences highlight aspects of each model that agree or disagree with the observed projections. The four models ...
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