Results 21 to 30 of about 135,414 (287)
Full-Waveform Inversion of Time-Lapse Crosshole GPR Data Using Markov Chain Monte Carlo Method
Remote Sensing, 2021 Crosshole ground-penetrating radar (GPR) is an important tool for a wide range of geoscientific and engineering investigations, and the Markov chain Monte Carlo (MCMC) method is a heuristic global optimization method that can be used to solve the ...
Shengchao Wang +5 more
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Nested Sequential Monte Carlo Methods
, 2015 We propose nested sequential Monte Carlo (NSMC), a methodology to sample from sequences of probability distributions, even where the random variables are high-dimensional. NSMC generalises the SMC framework by requiring only approximate, properly weighted, samples from the SMC proposal distribution, while still resulting in a correct SMC algorithm ...
Andersson Naesseth, Christian +2 more
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Efficient importance sampling in low dimensions using affine arithmetic [PDF]
, 2018 Despite the development of sophisticated techniques such as sequential Monte Carlo, importance sampling (IS) remains an important Monte Carlo method for low dimensional target distributions.
A Kong +18 more
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DYNAMIC PARAMETERS ESTIMATION OF INTERFEROMETRIC SIGNALS BASED ON SEQUENTIAL MONTE CARLO METHOD [PDF]
Научно-технический вестник информационных технологий, механики и оптики, 2014 The paper deals with sequential Monte Carlo method applied to problem of interferometric signals parameters estimation. The method is based on the statistical approximation of the posterior probability density distribution of parameters.
M. A. Volynsky +3 more
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Online sequential Monte Carlo smoother for partially observed diffusion processes
EURASIP Journal on Advances in Signal Processing, 2018 This paper introduces a new algorithm to approximate smoothed additive functionals of partially observed diffusion processes. This method relies on a new sequential Monte Carlo method which allows to compute such approximations online, i.e., as the ...
Pierre Gloaguen +2 more
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On the convergence of adaptive sequential Monte Carlo methods
The Annals of Applied Probability, 2016 In several implementations of Sequential Monte Carlo (SMC) methods it is natural, and important in terms of algorithmic efficiency, to exploit the information of the history of the samples to optimally tune their subsequent propagations. In this article we provide a carefully formulated asymptotic theory for a class of such \emph{adaptive} SMC methods.
Beskos, A +3 more
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A Semiautomatic Method for History Matching Using Sequential Monte Carlo [PDF]
SIAM/ASA Journal on Uncertainty Quantification, 2021 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Christopher C. Drovandi +2 more
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Energies, 2022 We present a data prepossessing method for parameter identification based on clustering and hypothesis testing in a power distribution network to successfully achieve a more accurate result.
Bin Li, Haoran Chen, Ke Hu
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A nonparametric ensemble transform method for Bayesian inference [PDF]
, 2013 Many applications, such as intermittent data assimilation, lead to a recursive application of Bayesian inference within a Monte Carlo context. Popular data assimilation algorithms include sequential Monte Carlo methods and ensemble Kalman filters (EnKFs).
Cotter C., Sebastian Reich
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СOMPUTATIONAL COMPLEXITY ANALYSIS OF RECURRENT DATA PROCESSING ALGORITHMS IN OPTICAL COHERENCE TOMOGRAPHY [PDF]
Научно-технический вестник информационных технологий, механики и оптики, 2014 The paper deals with the basic principles of signals representation in optical coherence tomography with the usage of dynamic systems theory formalism.
Maxim A. Volynsky +3 more
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