Search results for " approximation"

showing 10 items of 575 documents

Genetic algorithms for 3d reconstruction with supershapes

2009

Supershape model is a recent primitive that represents numerous 3D shapes with several symmetry axes. The main interest of this model is its capability to reconstruct more complex shape than superquadric model with only one implicit equation. In this paper we propose a genetic algorithms to re-construct a point cloud using those primitives. We used the pseudo-Euclidean distance to introduce a threshold to handle real data imperfection and speed up the process. Simulations using our proposed fitness functions and a fitness function based on inside-outside function show that our fitness function based on the pseudo-Euclidean distance performs better.

Mathematical optimizationFitness functionSpeedupImplicit functionFitness approximation3D reconstructionPoint cloudFunction (mathematics)Iterative reconstructionAlgorithmMathematics2009 16th IEEE International Conference on Image Processing (ICIP)
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On the approximability of the range assignment problem on radio networks in presence of selfish agents

2005

AbstractWe consider the range assignment problem in ad-hoc wireless networks in the context of selfish agents: A network manager aims to assigning transmission ranges to the stations in order to achieve strong connectivity of the network within a minimal overall power consumption. Station is not directly controlled by the manager and may refuse to transmit with a certain transmission range because it might be costly in terms of power consumption.We investigate the existence of payment schemes which induce the stations to follow the decisions of a network manager in computing a range assignment, that is, truthful mechanisms for the range assignment problem. We provide both positive and negat…

Mathematical optimizationGeneral Computer ScienceSettore INF/01 - Informaticabusiness.industryWireless networkApproximation algorithmContext (language use)Approximation algorithmsTheoretical Computer ScienceNetwork managementAlgorithmic mechanism design; Energy consumption in wireless networks; Approximation algorithmsEnergy consumption in wireless networksalgorithmic mechanism design; approximation algorithms; energy consumption in wireless networksbusinessTime complexityAssignment problemAlgorithmConnectivityAlgorithmic mechanism designAlgorithmic mechanism designMathematicsComputer Science(all)Theoretical Computer Science
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Numerical Approximation of Elliptic Variational Problems

2003

This chapter is dedicated to the study of Elliptic Variational Inequalities (EVI). Different forms of such an EVI are considered. The Ritz—Galerkin discretization method is introduced, and methods to approximate the solution of an EVI are presented. The finite dimensional subspaces are built by use of the Finite Element Method. The discretized problems are solved using variants of the Successive OverRelaxation (SOR) method. The algorithms are tested on a typical example. The way to develop computer programs is carefully analysed.

Mathematical optimizationMathematics::ProbabilityNumerical approximationDiscretizationVariational inequalityPendulum (mathematics)Interpolation operatorApplied mathematicsSeepage flowLinear subspaceFinite element methodMathematics
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Indirect Methods for Optimal Control Problems

2003

This chapter is dedicated to the numerical approximation of Optimal Control Problems. The algorithms are based on the necessary conditions for optimality which allow us to use a descent method for the minimization of the cost functional.

Mathematical optimizationNumerical approximationComputer scienceAdjoint equationMinificationOptimal controlDescent (mathematics)
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New analytical approach to analyze the nonlinear regime of stochastic resonance

2015

We propose some approximate methods to explore the nonlinear regime of the stochastic resonance phenomenon. These approximations correspond to different truncation schemes of cumulants. We compare the theoretical results for the signal power amplification, obtained by using ordinary cumulant truncation schemes, that is Gaussian and excess approximations, the modified two-state approximation with those obtained by numerical simulations of the Langevin equation describing the dynamics of the system.

Mathematical optimizationSettore FIS/02 - Fisica Teorica Modelli E Metodi MatematiciCumulant truncation scheme; modified two-state approximation; nonlinear regime; signal power amplification; stochastic resonance phenomenon; Electrical and Electronic Engineering; Acoustics and UltrasonicsCumulant truncation schemeAcoustics and UltrasonicsTruncationStochastic resonanceGaussianSignalPower (physics)Langevin equationsymbols.namesakeNonlinear systemstochastic resonance phenomenonsymbolsStatistical physicssignal power amplificationElectrical and Electronic Engineeringmodified two-state approximationnonlinear regimeCumulantMathematics
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A novel technique for stochastic root-finding: Enhancing the search with adaptive d-ary search

2017

The most fundamental problem encountered in the field of stochastic optimization, is the Stochastic Root Finding (SRF) problem where the task is to locate an unknown point x∗ for which g(x∗) = 0 for a given function g that can only be observed in the presence of noise [15]. The vast majority of the state-of-the-art solutions to the SRF problem involve the theory of stochastic approximation. The premise of the latter family of algorithms is to oper ate by means of so-called “small-step”processesthat explorethe search space in a conservative manner. Using this paradigm, the point investigated at any time instant is in the proximity of the point investigated at the previous time instant, render…

Mathematical optimizationStochastic point location problemsInformation Systems and ManagementLearning automataComputer scienceStochastic root finding problemsLearning Automata020206 networking & telecommunications02 engineering and technologyInterval (mathematics)Function (mathematics)Stochastic approximationComputer Science ApplicationsTheoretical Computer ScienceArtificial IntelligenceControl and Systems Engineering0202 electrical engineering electronic engineering information engineeringSearch problem020201 artificial intelligence & image processingStochastic optimizationAlgorithmRoot-finding algorithmSoftwareInformation Sciences
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ε-Regularized two-level optimization problems: Approximation and existence results

2006

The purpose of this work is to improve some results given in [12], relating to approximate solutions for two-level optimization problems. By considering an e-regularized problem, we get new properties, under convexity assumptions in the lower level problems. In particular, we prove existence results for the solutions to the e-regularized problem, whereas the initial two-level optimization problem may fail to have a solution. Finally, as an example, we consider an approximation method with interior penalty functions.

Mathematical optimizationVector optimizationWork (thermodynamics)Optimization problemL-reductionApproximation algorithmHardness of approximationConvexityPolynomial-time approximation schemeMathematics
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Approximation by mappings with singular Hessian minors

2018

Let $\Omega\subset\mathbb R^n$ be a Lipschitz domain. Given $1\leq p<k\leq n$ and any $u\in W^{2,p}(\Omega)$ belonging to the little H\"older class $c^{1,\alpha}$, we construct a sequence $u_j$ in the same space with $\operatorname{rank}D^2u_j<k$ almost everywhere such that $u_j\to u$ in $C^{1,\alpha}$ and weakly in $W^{2,p}$. This result is in strong contrast with known regularity behavior of functions in $W^{2,p}$, $p\geq k$, satisfying the same rank inequality.

Mathematics - Differential GeometryHessian matrix35B99 46T10Monge-Ampère equationRank (differential topology)Space (mathematics)01 natural sciencesHessian minorssymbols.namesakeMathematics - Analysis of PDEsLipschitz domainFOS: MathematicsMathematics::Metric GeometryAlmost everywhere0101 mathematicsMathematicsosittaisdifferentiaaliyhtälötDiscrete mathematicsSequenceApplied Mathematicsta111010102 general mathematics16. Peace & justiceFunctional Analysis (math.FA)nonlinear approximationMathematics - Functional Analysis010101 applied mathematicsDifferential Geometry (math.DG)symbolsfunktionaalianalyysiAnalysisAnalysis of PDEs (math.AP)Nonlinear Analysis
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Computing continuous numerical solutions of matrix differential equations

1995

Abstract In this paper, we construct analytical approximate solutions of initial value problems for the matrix differential equation X ′( t ) = A ( t ) X ( t ) + X ( t ) B ( t ) + L ( t ), with twice continuously differentiable functions A ( t ), B ( t ), and L ( t ), continuous. We determine, in terms of the data, the existence interval of the problem. Given an admissible error e, we construct an approximate solution whose error is smaller than e uniformly, in all the domain.

Matrix differential equationDifferential equationNumerical solutionSpline functionMathematical analysisMinimax approximation algorithmComputational MathematicsSpline (mathematics)Matrix (mathematics)Initial value problemComputational Theory and MathematicsModelling and SimulationMatrix differential equationModeling and SimulationError boundInitial value problemApproximate solutionLinear equationMathematicsComputers &amp; Mathematics with Applications
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Competing species system as a qualitative model of radiation therapy

2016

To examine complex features of tumor dynamics we analyze a competing-species lattice model that takes into account the competition for nutrients or space as well as interaction with therapeutic factors such as drugs or radiation. Our model might be interpreted as a certain prey–predator system having three trophic layers: (i) the basal species that might be interpreted as nutrients; (ii) normal and tumor cells that consume nutrients, and (iii) therapeutic factors that might kill either nutrient, normal or tumor cells. Using a wide spectrum of parameters we examined survival of our species and tried to identify the corresponding dynamical regimes. It was found that the radiotherapy influence…

Mean-field approximationPrey–predator systemsTumor growthMonte Carlo simulationsPhysica A : Statistical Mechanics and Its Applications
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