Results 11 to 20 of about 1,239,591 (239)
SMCTC: Sequential Monte Carlo in C++ [PDF]
Journal of Statistical Software, 2009 Sequential Monte Carlo methods are a very general class of Monte Carlo methodsfor sampling from sequences of distributions. Simple examples of these algorithms areused very widely in the tracking and signal processing literature.
Adam M. Johansen
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Mobility Tracking in Cellular Networks with Sequential Monte Carlo Filters [PDF]
, 2005 This paper considers mobility tracking in wireless communication networks based on received signal strength indicator measurements. Mobility tracking involves on-line estimation of the position and speed of a mobile unit.
Angelova, D. +3 more
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High performance Monte Carlo computation for finance risk data analysis [PDF]
, 2013 This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Finance risk management has been playing an increasingly important role in the finance sector, to analyse finance data and to prevent any potential crisis ...
Zhao, Yu
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Crossed source-detector geometry for a novel spray diagnostic: Monte Carlo simulation and analytical results [PDF]
, 2005 Sprays and other industrially relevant turbid media can be quantitatively characterized by light scattering. However, current optical diagnostic techniques generate errors in the intermediate scattering regime where the average number of light ...
Churmakov, D. Y. +4 more
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Stochastic Definition of State-Space Equation for Particle Filtering Algorithms
Chemical Engineering Transactions, 2013 Particle Filtering is a nonlinear and non-Gaussian model-based Bayesian Filtering algorithm based on Monte Carlo Sampling techniques. This filtering methodology can be used to increase the reliability and the availability of the monitored system ...
M. Corbetta +3 more
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World Electric Vehicle Journal, 2023 An autonomous car must know where it is with high precision in order to maneuver safely and reliably in both urban and highway environments. Thus, in this paper, a reliable and relatively precise position estimation (localization) technique for ...
Wael A. Farag, Julien Moussa H. Barakat
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Why Monte Carlo Simulations are Inferences and not Experiments [PDF]
, 2012 Monte Carlo Simulations arrive at their results by introducing randomness, sometimes derived from a physical randomizing device. Nonetheless, we argue, they open no new epistemic channels beyond that already employed by traditional simulations: the ...
John D. Norton +3 more
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Markov chain Monte Carlo methods for state-space models with point process observations [PDF]
, 2012 This letter considers how a number of modern Markov chain Monte Carlo (MCMC) methods can be applied for parameter estimation and inference in state-space models with point process observations.
Niranjan, Mahesan +2 more
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Single flavour filtering for RHMC in BQCD
EPJ Web of Conferences, 2018 Filtering algorithms for two degenerate quark flavours have advanced to the point that, in 2+1 flavour simulations, the cost of the strange quark is significant compared with the light quarks.
Kamleh Waseem +3 more
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A Modification of the Monte Carlo Filtering Approach for Correcting Negative SEA Loss Factors
Acoustics, 2022 Monte Carlo Filtering (MCF) is one of the methods of Experimental Statistical Energy Analysis (E-SEA), which allows the correction of negative LFs (Loss Factors).
Paweł Nieradka, Andrzej Dobrucki
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