Search results for "convex"

showing 10 items of 389 documents

A quantitative reverse Faber-Krahn inequality for the first Robin eigenvalue with negative boundary parameter

2021

The aim of this paper is to prove a quantitative form of a reverse Faber-Krahn type inequality for the first Robin Laplacian eigenvalueλβwith negative boundary parameter among convex sets of prescribed perimeter. In that framework, the ball is the only maximizer forλβand the distance from the optimal set is considered in terms of Hausdorff distance. The key point of our stategy is to prove a quantitative reverse Faber-Krahn inequality for the first eigenvalue of a Steklov-type problem related to the original Robin problem.

Control and Optimizationconvex setsBoundary (topology)variaatiolaskenta01 natural sciencesSet (abstract data type)Perimeter0103 physical sciencesquantitative isoperimetric inequalityConvex setBall (mathematics)0101 mathematicsEigenvalues and eigenvectorsMathematicsosittaisdifferentiaaliyhtälötominaisarvot010102 general mathematicsMathematical analysisRegular polygonMathematics::Spectral Theorymatemaattinen optimointiQuantitative isoperimetric inequalityComputational MathematicsHausdorff distanceControl and Systems EngineeringRobin eigenvalue010307 mathematical physicsLaplace operator
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An Adaptive Alternating Direction Method of Multipliers

2021

AbstractThe alternating direction method of multipliers (ADMM) is a powerful splitting algorithm for linearly constrained convex optimization problems. In view of its popularity and applicability, a growing attention is drawn toward the ADMM in nonconvex settings. Recent studies of minimization problems for nonconvex functions include various combinations of assumptions on the objective function including, in particular, a Lipschitz gradient assumption. We consider the case where the objective is the sum of a strongly convex function and a weakly convex function. To this end, we present and study an adaptive version of the ADMM which incorporates generalized notions of convexity and penalty…

Control and Optimizationsignal denoisingApplied Mathematicsalternating direction method of multipliersMathematics::Optimization and Controldouglas–rachford algorithmUNESCO::CIENCIAS TECNOLÓGICASManagement Science and Operations Researchcomonotonicityweakly convex functionOptimization and Control (math.OC)47H05 47N10 47J25 49M27 65K15FOS: Mathematicsfirm thresholdingMathematics - Optimization and Control
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Convergence Theorems for Varying Measures Under Convexity Conditions and Applications

2022

AbstractIn this paper, convergence theorems involving convex inequalities of Copson’s type (less restrictive than monotonicity assumptions) are given for varying measures, when imposing convexity conditions on the integrable functions or on the measures. Consequently, a continuous dependence result for a wide class of differential equations with many interesting applications, namely measure differential equations (including Stieltjes differential equations, generalized differential problems, impulsive differential equations with finitely or countably many impulses and also dynamic equations on time scales) is provided.

Convergence of measuresconvex inequalitymeasure differential equationsSettore MAT/05 - Analisi MatematicaGeneral Mathematicscontinuous dependence
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Quantifying brain tumor tissue abundance in HR-MAS spectra using non-negative blind source separation techniques

2012

Given high-resolution magic angle spinning (HR-MAS) spectra from several glial tumor subjects, our goal is to differentiate between tumor tissue types by separating the different sources that contribute to the profile of each spectrum. Blind source separation techniques are applied for obtaining characteristic profiles for necrosis, highly cellular tumor and border tumor tissue and providing the contribution (abundance) of each of these tumor tissue types to the profile of each spectrum. The problem is formulated as a non-negative source separation problem. Non-negative matrix factorization, convex analysis of non-negative sources and non-negative independent component analysis methods are …

Convex analysisApplied MathematicsAnalytical chemistryGlial tumorIndependent component analysisBlind signal separation030218 nuclear medicine & medical imagingAnalytical ChemistryMatrix decomposition03 medical and health sciences0302 clinical medicineDimension (vector space)Magic angle spinningSource separationBiological system030217 neurology & neurosurgeryMathematicsJournal of Chemometrics
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On the number of singularities, zero curvature points and vertices of a simple convex space curve

1995

We prove a generalization of the 4 vertex theorem forC3 closed simple convex space curves including singular and zero curvature points.

Convex analysisCombinatoricsFundamental theorem of curvesConvex polytopeConvex curveMathematical analysisConvex setTotal curvatureFour-vertex theoremGeometry and TopologyCurvatureMathematicsJournal of Geometry
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Constrained control of a nonlinear two point boundary value problem, I

1994

In this paper we consider an optimal control problem for a nonlinear second order ordinary differential equation with integral constraints. A necessary optimality condition in form of the Pontryagin minimum principle is derived. The proof is based on McShane-variations of the optimal control, a thorough study of their behaviour in dependence of some denning parameters, a generalized Green formula for second order ordinary differential equations with measurable coefficients and certain tools of convex analysis.

Convex analysisControl and OptimizationApplied MathematicsMathematical analysisExact differential equationManagement Science and Operations ResearchOptimal controlComputer Science ApplicationsNonlinear systemOrdinary differential equationOrder (group theory)Initial value problemBoundary value problemMathematicsJournal of Global Optimization
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A four vertex theorem for strictly convex space curves

1993

Convex analysisDiscrete mathematicsConvex hullConvex setSpace curfFour-vertex theoremVertex theoremKrein–Milman theoremConvex spaceStrictly convex spaceVertex (curve)Danskin's theoremGeometry and TopologyMathematics
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Locally Convex Quasi *-Algebras of Operators

2011

This note is mainly concerned with locally convex quasi C*-normed *-algebras which arise as completions of C*-algebras of operators under certain topologies. Their importance is made clear by the representation theory of abstract locally convex quasi C*-normed *-algebras, investigated in previous papers and whose basic aspects are also overviewed here.

Convex analysisDiscrete mathematicsQuasi *-algebrasPure mathematicsApplied MathematicsRegular polygonSubderivativeOperator theoryNetwork topologyRepresentation theoryComputational MathematicsComputational Theory and MathematicsSettore MAT/05 - Analisi MatematicaOperatorMathematicsComplex Analysis and Operator Theory
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On the Euler-Lagrange inequality of a convex variational integral in Orlicz spaces

1987

Convex analysisInequalitymedia_common.quotation_subjectMathematical analysisRegular polygonLinear matrix inequalityMinkowski inequalityGeneral Earth and Planetary SciencesApplied mathematicsBirnbaum–Orlicz spaceLp spaceJensen's inequalityGeneral Environmental Sciencemedia_commonMathematicsBanach Center Publications
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Fixed point theory for almost convex functions

1998

Traditionally, metric fixed point theory has sought classes of spaces in which a given type of mapping (nonexpansive, assymptotically or generalized nonexpansive, uniformly Lipschitz, etc.) from a nonempty weakly compact convex set into itself always has a fixed point. In some situations the class of space is determined by the application while there is some degree of freedom in constructing the map to be used. With this in mind we seek to relax the conditions on the space by considering more restrictive types of mappings.

Convex analysisLeast fixed pointPure mathematicsApplied MathematicsMathematical analysisConvex setSubderivativeAbsolutely convex setFixed pointKakutani fixed-point theoremFixed-point propertyAnalysisMathematics
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