Search results for "kernel"

showing 7 items of 357 documents

Iterative Reconstruction of Memory Kernels.

2017

In recent years, it has become increasingly popular to construct coarse-grained models with non-Markovian dynamics to account for an incomplete separation of time scales. One challenge of a systematic coarse-graining procedure is the extraction of the dynamical properties, namely, the memory kernel, from equilibrium all-atom simulations. In this article, we propose an iterative method for memory reconstruction from dynamical correlation functions. Compared to previously proposed noniterative techniques, it ensures by construction that the target correlation functions of the original fine-grained systems are reproduced accurately by the coarse-grained system, regardless of time step and disc…

Mathematical optimization010304 chemical physicsDiscretizationGeneralizationComputer scienceIterative methodFOS: Physical sciences02 engineering and technologyIterative reconstructionConstruct (python library)Condensed Matter - Soft Condensed Matter021001 nanoscience & nanotechnology01 natural sciencesComputer Science ApplicationsKernel (image processing)Integrator0103 physical sciencesVerlet integrationSoft Condensed Matter (cond-mat.soft)Physical and Theoretical Chemistry0210 nano-technologyAlgorithmJournal of chemical theory and computation
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On the CAT(0) dimension of 2-dimensional Bestvina-Brady groups

2002

Let K be a 2-dimensional finite flag complex. We study the CAT(0) dimension of the `Bestvina-Brady group', or `Artin kernel', Gamma_K. We show that Gamma_K has CAT(0) dimension 3 unless K admits a piecewise Euclidean metric of non-positive curvature. We give an example to show that this implication cannot be reversed. Different choices of K lead to examples where the CAT(0) dimension is 3, and either (i) the geometric dimension is 2, or (ii) the cohomological dimension is 2 and the geometric dimension is not known.

nonpositive curvatureGroup (mathematics)20F6720F67 57M20Geometric Topology (math.GT)Group Theory (math.GR)Cohomological dimensionEuclidean distanceCombinatoricsKernel (algebra)Mathematics::Group TheoryMathematics - Geometric Topologydimension57M20Dimension (vector space)FOS: MathematicsArtin groupflag complexGeometry and TopologyArtin groupMathematics - Group TheoryZero-dimensional spaceMathematicsFlag (geometry)
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Fuzzy-based Kernel Regression Approaches for Free Form Deformation and Elastic Registration of Medical Images

2009

In modern medicine, a largely diffused method for gathering knowledge about organs and tissues is obtained by means of merging information from several datasets. Such data are provided from multimodal or sequential acquisitions. As a consequence, a pre-processing step that is called “image registration” is required to achieve data integration. Image registration aims to obtain the best possible spatial correspondence between misaligned datasets. This procedure is also useful to correct distortions induced by magnetic interferences with the acquisition equipment signals or the ones due patient’s involuntary movements such as heartbeat or breathing. The problem can be regarded as finding the …

elastic registrationbusiness.industryKernel regressionFree-form deformationPattern recognitionArtificial intelligencebusinessFuzzy logicMathematics
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Efficient remote sensing image classification with Gaussian processes and Fourier features

2017

This paper presents an efficient methodology for approximating kernel functions in Gaussian process classification (GPC). Two models are introduced. We first include the standard random Fourier features (RFF) approximation into GPC, which largely improves the computational efficiency and permits large scale remote sensing data classification. In addition, we develop a novel approach which avoids randomly sampling a number of Fourier frequencies, and alternatively learns the optimal ones using a variational Bayes approach. The performance of the proposed methods is illustrated in complex problems of cloud detection from multispectral imagery.

010504 meteorology & atmospheric sciencesContextual image classificationComputer scienceMultispectral imageData classification0211 other engineering and technologiesSampling (statistics)02 engineering and technology01 natural sciencessymbols.namesakeBayes' theoremFourier transformKernel (statistics)symbolsGaussian process021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing
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Riemann-Hilbert approach to the time-dependent generalized sine kernel

2011

We derive the leading asymptotic behavior and build a new series representation for the Fredholm determinant of integrable integral operators appearing in the representation of the time and distance dependent correlation functions of integrable models described by a six-vertex R-matrix. This series representation opens a systematic way for the computation of the long-time, long-distance asymptotic expansion for the correlation functions of the aforementioned integrable models away from their free fermion point. Our method builds on a Riemann–Hilbert based analysis.

Pure mathematicsSeries (mathematics)Integrable systemGeneral MathematicsGeneral Physics and AstronomyFredholm determinantRiemann hypothesissymbols.namesakeKernel (statistics)symbolsSineRepresentation (mathematics)Asymptotic expansionMathematicsAdvances in Theoretical and Mathematical Physics
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Broglie and Young, visionaries who shed light in the polar topology that grounds our reality: a hypothesis

2020

Una observación matemática que relaciona los patrones fractales y la operación de convolución en el contexto del procesamiento de imágenes digitales interrumpió una investigación que nos lleva a plantear la hipótesis de que el concepto de onda de materia (o dualidad onda-partícula) se encuentra en la dicotomía entre el par débil y un topología fuerte en el ámbito del marco de atractores singulares continuos en ninguna parte diferenciables y el concepto de fotón-solitón de Vigier. Tal inferencia parece ser más evidente en la interpretación de Broglie-Bohm de la mecánica cuántica en el cruce de características locales x globales. De esto se deduce también que la relación de los fenómenos natu…

staircase functionsreproducing kernelnormally hyperbolic invariant manifoldsnormal topologyUNESCO::FÍSICAtotal variation filteringconvergence of power seriessmall-divisorssurface of controlevel-set methods:FÍSICA [UNESCO]lebesgue-cantor measurearithmetic physicsinteracting ieldperturbation theory
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An Observation Framework for Multi-Agent Systems

2009

Existing middleware platforms for multi-agent systems (MAS) do not provide general support for observation. On the other hand, observation is considered to be an important mechanism needed for realizing effective and efficient coordination of agents. This paper describes a framework called Agent Observable Environment (AOE) for observation-based interaction in MAS. The framework provides 1) possibility to model MAS components with RDFbased observable soft-bodies, 2) support for both query and publish/subscribe style ontology-driven observation, and 3) ability to restrict the visibility of observable information using observation rules. Additionally, we report on an implementation of the fra…

agent observable environmentMASobservationJADEsoft-bodycustom kernel serviceontology-driven observationontologiesmulti-agent systemsartificial intelligenceComputingMethodologies_ARTIFICIALINTELLIGENCE
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