Search results for "65"

showing 10 items of 1111 documents

Coupled conditional backward sampling particle filter

2020

The conditional particle filter (CPF) is a promising algorithm for general hidden Markov model smoothing. Empirical evidence suggests that the variant of CPF with backward sampling (CBPF) performs well even with long time series. Previous theoretical results have not been able to demonstrate the improvement brought by backward sampling, whereas we provide rates showing that CBPF can remain effective with a fixed number of particles independent of the time horizon. Our result is based on analysis of a new coupling of two CBPFs, the coupled conditional backward sampling particle filter (CCBPF). We show that CCBPF has good stability properties in the sense that with fixed number of particles, …

65C05FOS: Computer and information sciencesStatistics and ProbabilityunbiasedMarkovin ketjutTime horizonStatistics - Computation01 natural sciencesStability (probability)backward sampling65C05 (Primary) 60J05 65C35 65C40 (secondary)010104 statistics & probabilityconvergence rateFOS: MathematicsApplied mathematics0101 mathematicscouplingHidden Markov model65C35Computation (stat.CO)Mathematicsstokastiset prosessitBackward samplingSeries (mathematics)Probability (math.PR)Sampling (statistics)conditional particle filterMonte Carlo -menetelmätRate of convergence65C6065C40numeerinen analyysiStatistics Probability and UncertaintyParticle filterMathematics - ProbabilitySmoothing
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Uncertainty quantification on a spatial Markov-chain model for the progression of skin cancer

2019

AbstractA spatial Markov-chain model is formulated for the progression of skin cancer. The model is based on the division of the computational domain into nodal points, that can be in a binary state: either in ‘cancer state’ or in ‘non-cancer state’. The model assigns probabilities for the non-reversible transition from ‘non-cancer’ state to the ‘cancer state’ that depend on the states of the neighbouring nodes. The likelihood of transition further depends on the life burden intensity of the UV-rays that the skin is exposed to. The probabilistic nature of the process and the uncertainty in the input data is assessed by the use of Monte Carlo simulations. A good fit between experiments on mi…

65C05Skin NeoplasmsComputer scienceQuantitative Biology::Tissues and OrgansMarkovin ketjut0206 medical engineeringMonte Carlo methodPhysics::Medical PhysicsBinary number02 engineering and technologyArticleihosyöpä03 medical and health sciencesMicemedicineAnimalsHumansComputer SimulationStatistical physicsUncertainty quantification60J20stokastiset prosessit030304 developmental biologyProbability0303 health sciencesMarkov chainApplied MathematicsProbabilistic logicUncertaintyState (functional analysis)medicine.disease020601 biomedical engineeringAgricultural and Biological Sciences (miscellaneous)Markov ChainsCardinal pointModeling and Simulation65C40Disease Progressionmatemaattiset mallitSkin cancerMonte Carlo MethodJournal of Mathematical Biology
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From Feynman–Kac formulae to numerical stochastic homogenization in electrical impedance tomography

2016

In this paper, we use the theory of symmetric Dirichlet forms to derive Feynman–Kac formulae for the forward problem of electrical impedance tomography with possibly anisotropic, merely measurable conductivities corresponding to different electrode models on bounded Lipschitz domains. Subsequently, we employ these Feynman–Kac formulae to rigorously justify stochastic homogenization in the case of a stochastic boundary value problem arising from an inverse anomaly detection problem. Motivated by this theoretical result, we prove an estimate for the speed of convergence of the projected mean-square displacement of the underlying process which may serve as the theoretical foundation for the de…

65C05Statistics and Probability65N21stochastic homogenizationquantitative convergence result01 natural sciencesHomogenization (chemistry)78M40general reflecting diffusion process010104 statistics & probabilitysymbols.namesakeFeynman–Kac formula60J4535Q60Applied mathematicsFeynman diagramBoundary value problemSkorohod decomposition0101 mathematicsElectrical impedance tomographyBrownian motionMathematicsrandom conductivity field65N75010102 general mathematicsFeynman–Kac formulaLipschitz continuityBounded functionstochastic forward problemsymbols60J55Statistics Probability and Uncertainty60H30electrical impedance tomographyThe Annals of Applied Probability
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An elementary formula for computing shape derivatives of EFIE system matrix

2012

We derive analytical shape derivative formulas of the system matrix representing electric field integral equation discretized with Raviart-Thomas basis functions. The arising integrals are easy to compute with similar methods as the entries of the original system matrix. The results are compared to derivatives computed with automatic differentiation technique and finite differences, and are found to be in excellent agreement.

65M38 (Primary) 35Q93 49Q10 (Secondary)FOS: MathematicsNumerical Analysis (math.NA)Mathematics - Numerical Analysis
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Guaranteed error control bounds for the stabilised space-time IgA approximations to parabolic problems

2017

The paper is concerned with space-time IgA approximations of parabolic initial-boundary value problems. We deduce guaranteed and fully computable error bounds adapted to special features of IgA approximations and investigate their applicability. The derivation method is based on the analysis of respective integral identities and purely functional arguments. Therefore, the estimates do not contain mesh-dependent constants and are valid for any approximation from the admissible (energy) class. In particular, they provide computable error bounds for norms associated with stabilised space-time IgA approximations as well as imply efficient error indicators enhancing the performance of fully adap…

65N15 65N25 65N35F.2.1; G.1.0; G.1.2; G.1.3; G.1.8; B.2.3Computer Science - Numerical AnalysisG.1.8B.2.3FOS: MathematicsG.1.2Mathematics - Numerical AnalysisF.2.1G.1.3Numerical Analysis (math.NA)G.1.0
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Sublimation of icy aggregates in the coma of comet 67P/Churyumov–Gerasimenko detected with the OSIRIS cameras on board Rosetta

2016

Beginning in 2014 March, the OSIRIS (Optical, Spectroscopic, and Infrared Remote Imaging System) cameras began capturing images of the nucleus and coma (gas and dust) of comet 67P/Churyumov¿Gerasimenko using both the wide angle camera (WAC) and the narrow angle camera (NAC). The many observations taken since July of 2014 have been used to study the morphology, location, and temporal variation of the comet's dust jets. We analysed the dust monitoring observations shortly after the southern vernal equinox on 2015 May 30 and 31 with the WAC at the heliocentric distance Rh = 1.53 AU, where it is possible to observe that the jet rotates with the nucleus. We found that the decline of brightness a…

67P/Churyumov-GerasimenkoBrightness010504 meteorology & atmospheric sciences530 PhysicsInfraredCometdata analysis[SDU.ASTR.EP]Sciences of the Universe [physics]/Astrophysics [astro-ph]/Earth and Planetary Astrophysics [astro-ph.EP]Narrow angleComets: individual: 67P/Churyumov-Gerasimenko; Methods: data analysis; Methods: numerical; Methods: observationalFOS: Physical sciencesEquinoxAstrophysics01 natural sciencesAstronomi astrofysik och kosmologiMethods: observationalMethods: data analysisindividual: 67P/Churyumov-Gerasimenko [Comets]0103 physical sciencesAstronomy Astrophysics and Cosmologyobservational [Methods]cometsdata analysis [Methods]010303 astronomy & astrophysics0105 earth and related environmental sciencesobservational method: numerical methodPhysicsEarth and Planetary Astrophysics (astro-ph.EP)Comets: individual: 67P/Churyumov-Gerasimenkomethods: data analysis methods: numerical methods: observational comets: individual: 67P/Churyumov–Gerasimenkonumerical [Methods]biology[SDU.ASTR]Sciences of the Universe [physics]/Astrophysics [astro-ph]Methods: numerical520 AstronomyAstronomyAstronomy and Astrophysics620 Engineeringbiology.organism_classificationOn boardSpace and Planetary Science[SDU]Sciences of the Universe [physics]Sublimation (phase transition)QB651OsirisAstrophysics - Earth and Planetary Astrophysics
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"Table 8" of "Measurements of the line shape of the Z0 and determination of electroweak parameters from its hadronic and leptonic decays"

1994

E+ E- forward-backward asymmetries from the 1991 data set for both final state fermions in the polar angle range 44 to 136 degrees and accollinearity < 10 degrees (the s + t data). Additional systematic error, excluding luminosity, is 0.002.

88.465-93.703E+ E- --> E+ E-Electron productionElasticAsymmetry MeasurementE+ E- --> Z0E+ E- ScatteringExclusiveHigh Energy Physics::ExperimentASYM
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"Table 10" of "Measurements of the line shape of the Z0 and determination of electroweak parameters from its hadronic and leptonic decays"

1994

E+ E- forward-backward asymmetries from the 1991 data set after t-channel subtraction with only the E- constraint by polar angle 44 to 136 degrees and accollinearity < 10 degrees. Additional systematic error, excluding luminosity, is 0.003 at the peak.

88.465-93.703E+ E- --> E+ E-Electron productionElasticAsymmetry MeasurementE+ E- --> Z0E+ E- ScatteringExclusiveHigh Energy Physics::ExperimentASYM
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"Table 4" of "Measurements of the line shape of the Z0 and determination of electroweak parameters from its hadronic and leptonic decays"

1994

E+ E- cross sections from the 1991 data set for both final state fermions in the polar angle range 44 to 136 degrees and accollinearity < 10 degrees (the s + t data). Additional systematic error, excluding luminosity, is 0.37 pct.

88.465-93.703E+ E- --> E+ E-Electron productionElasticE+ E- --> Z0E+ E- ScatteringIntegrated Cross SectionExclusiveCross SectionSIG
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"Table 6" of "Measurements of the line shape of the Z0 and determination of electroweak parameters from its hadronic and leptonic decays"

1994

E+ E- cross sections from the 1991 data set after t-channel subtraction with only the E- constraint by polar angle 44 to 136 degrees and accollinearity < 10 degrees. Additional systematic error, excluding luminosity, is 0.5 pct at the peak.

88.465-93.703E+ E- --> E+ E-Electron productionElasticE+ E- --> Z0E+ E- ScatteringIntegrated Cross SectionExclusiveCross SectionSIG
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