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projection on convex sets

Rapid Magnetic Resonance Imaging Using Undersampled Projection-Onto-Convex-Sets Reconstruction Mohammad Sabati* 1,2 , Leila Borvayeh 3

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

Projection onto Convex Sets Method in Spacefrequency Domain for Super Resolution

... [12-15], Projection onto Convex Sets (POCS) [16-18], Maximum a Posteriori [19-22], Iterative Back Projection [23-25], and their combination ...

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Implementation of a projection onto convex sets iteration based image coder

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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Fitting Convex Sets to Data: Algorithms and Applications

Fitting Convex Sets to Data: Algorithms and Applications

... on convex optimization, and the types of guarantees obtained in [151] are qualitatively quite different in comparison to ...a projection along the di- rection of change yields an algorithm with a recovery ...

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Functionally closed sets and functionally convex sets in real Banach spaces

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

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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Super Resolution of an Image using Projection onto Convex Set Algorithm

Super Resolution of an Image using Projection onto Convex Set Algorithm

... The term POCS is derived from two basic terms name ly convex sets and projections. POCS is having large number of applications in Papoulis-Gerchberg Algorithm, Neural Network Associative Memory, Resolution ...

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A simple algorithm for computing projection onto intersection of finite level sets

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

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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On the Convex Feasibility Problem

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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General Reflexivity For Absolutely Convex Sets, Mahtab Lak

General Reflexivity For Absolutely Convex Sets, Mahtab Lak

... Suppose (X, Y, E) is a reflexivity triple and A ⊂ X is ac-E-reflexive. We say that A is heredi- tarily ac-E-reflexive if and only if every σ (X, Y )-closed absolutely convex subset of A is ac-E- reflexive. For ...

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Optimal Separation of Twin Convex Sets under Externalities

Optimal Separation of Twin Convex Sets under Externalities

... Optimization and rules for decentralization in economic theory of choice and decision making rely heavily on convexity which naturally arises in the underlying preferences, budget sets, production sets and ...

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On hyperspaces of max-plus and max-min convex sets

On hyperspaces of max-plus and max-min convex sets

... max-min convex sets. They are counterparts of the convex sets in the idempotent mathematics, ...max-plus convex sets as well as survey of results in max-plus convexity can be ...

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Notions of generalized s convex functions on fractal sets

Notions of generalized s convex functions on fractal sets

... generalized convex functions, however, one of the most famous is known as the general- ized Hermit-Hadamard inequality, or the ‘generalized Hadamard inequality’ and stated as follows (see []): let f be a ...

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A convergence result on random products of mappings in metric trees

A convergence result on random products of mappings in metric trees

... Remark 3.1 . In [14]the authors made heavy use of the property that in smooth reflex- ive Banach spaces X, if E is a closed subspace of X, then there is at most one nonexpan- sive retraction of X onto E [26]. In the case ...

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Some fixed point theorems in locally p-convex spaces

Some fixed point theorems in locally p-convex spaces

... Maki [] introduced the notion of minimal spaces which is a generalization of the con- cept of topological spaces (see also []). After these initial papers, many authors have paid attention to the subject and have ...

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Regularized gradient projection methods for equilibrium and constrained convex minimization problems

Regularized gradient projection methods for equilibrium and constrained convex minimization problems

... In this article, based on Marino and Xu’s method, an iterative method which combines the regularized gradient-projection algorithm (RGPA) and the averaged mappings approach is proposed for finding a common solution ...

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Computing Convex Coverage Sets for Faster Multi-objective Coordination

Computing Convex Coverage Sets for Faster Multi-objective Coordination

... The CCS has not previously been considered as a solution concept for MO-CoGs because computing a CCS requires running linear programs, whilst computing a PCS requires only pairwise comparisons of solutions. However, a ...

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On mean curvature integrals of the outer parallel body of the projection of a convex body

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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