Results 21 to 30 of about 136,829,320 (227)
Maximum likelihood parameter estimation for latent variable models using sequential Monte Carlo [PDF]
, 2006 We present a sequential Monte Carlo (SMC) method for maximum likelihood (ML) parameter estimation in latent variable models. Standard methods rely on gradient algorithms such as the ExpectationMaximization (EM) algorithm and its Monte Carlo variants. Our
Davy, Manuel +12 more
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Maximum a posteriori vs maximum probability recursive sparse estimation [PDF]
2009 European Control Conference (ECC), 2009 Recursive sparse parameter estimates obtained using the author's recent maximum a posteriori (MAP) approach, where the sparse parameter estimates are determined as the a posteriori mode of a Gaussian sum filter, are compared with a new maximum probability (MP) methodology, where the sparse parameter estimates are determined as the component of a ...
Lachlan Blackhall, Michael Rotkowitz
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Maximum-a-Posteriori Estimation with Bayesian Confidence Regions [PDF]
SIAM Journal on Imaging Sciences, 2017 Solutions to inverse problems that are ill-conditioned or ill-posed may have significant intrinsic uncertainty. Unfortunately, analyzing and quantifying this uncertainty is very challenging, particularly in high-dimensional problems. As a result, while most modern mathematical imaging methods produce impressive point estimation results, they are ...
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Adaptive QRS Detection Based on Maximum A Posteriori Estimation [PDF]
IEEE Transactions on Biomedical Engineering, 1982 A mathematical model for the occurrence of nonoverlapping pulse-shaped waveforms corrupted with colored Gaussian noise is considered for the purpose of QRS detection. The number of waveforms, the arrival times, amplitudes, and widths are regarded as random variables.
Börjesson, Per Ola +3 more
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Applications of single valued trapezoidal neutrosophic maximum a posteriori estimation in real-life problems [PDF]
Journal of Fuzzy Extension and ApplicationsIn this paper, we introduce Single-Valued Trapezoidal Neutrosophic Maximum a Posteriori (SVTN-MAP) estimation to deal with uncertainty in prior distribution parameters, where prior parameters are assumed to be Single-Valued Trapezoidal Neutrosophic ...
Nizar Altounji +2 more
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Leida xuebao, 2017 The multi-baseline InSAR can effectively reduce the adverse effect caused by the abrupt change of the target and the large noise disturbance and can obtain the Digital Elevation Model (DEM) that is more accurate than the single baseline InSAR ...
Si Qi +4 more
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CPT: Pharmacometrics & Systems Pharmacology, 2021 Model‐informed precision dosing (MIPD) approaches typically apply maximum a posteriori (MAP) Bayesian estimation to determine individual pharmacokinetic (PK) parameters with the goal of optimizing future dosing regimens.
Jasmine H. Hughes, Ron J. Keizer
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A Posteriori Error Estimates in the Maximum Norm for Parabolic Problems [PDF]
SIAM Journal on Numerical Analysis, 2009 We derive a posteriori error estimates in the $L_\infty((0,T];L_\infty(\Omega))$ norm for approximations of solutions to linear parabolic equations. Using the elliptic reconstruction technique introduced by Makridakis and Nochetto and heat kernel estimates for linear parabolic problems, we first prove a posteriori bounds in the maximum norm for ...
Alan Demlow +2 more
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On Maximum a Posteriori Estimation of Hidden Markov Processes
CoRR, 2009 We present a theoretical analysis of Maximum a Posteriori (MAP) sequence estimation for binary symmetric hidden Markov processes. We reduce the MAP estimation to the energy minimization of an appropriately defined Ising spin model, and focus on the performance of MAP as characterized by its accuracy and the number of solutions corresponding to a ...
Armen E. Allahverdyan, Aram Galstyan
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Signal waveform estimation in the presence of uncertainties about the steering vector [PDF]
, 2004 We consider the problem of signal waveform estimation using an array of sensors where there exist uncertainties about the steering vector of interest. This problem occurs in many situations, including arrays undergoing deformations, uncalibrated arrays ...
Chalus, Christophe +2 more
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