Buscar
Mostrando ítems 1-10 de 311
String-averaging expectation-maximization for maximum likelihood estimation in emission tomography
(Iop Publishing Ltd, 2014-05-01)
We study the maximum likelihood model in emission tomography and propose a new family of algorithms for its solution, called string-averaging expectation maximization (SAEM). In the string-averaging algorithmic regime, the ...
String-averaging expectation-maximization for maximum likelihood estimation in emission tomography
(IOP PublishingBristol, 2014-04-17)
We study the maximum likelihood model in emission tomography and propose a new family of algorithms for its solution, called string-averaging expectation-maximization (SAEM). In the string-averaging algorithmic regime, the ...
String-averaging expectation-maximization for maximum likelihood estimation in emission tomography
(Iop Publishing Ltd, 2014)
Fast EM-like methods for maximum "a posteriori" estimates in emission tomography
(Ieee-inst Electrical Electronics Engineers IncNew YorkEUA, 2001)
String-averaging expectation-maximization for maximum likelihood estimation in emission tomography
(Iop Publishing Ltd, 2014)
Energy distribution of the neutron flux measurements at the chilean reactor RECH-1 using multi-foil neutron activation and the expectation maximization unfolding algorithm
(Elsevier, 2017)
We present a methodology to obtain the energy distribution of the neutron flux of an experimental nuclear reactor, using multi-foil activation measurements and the Expectation Maximization unfolding algorithm, which is ...
A row-action alternative to the EM algorithm for maximizing likelihoods in emission tomography
(Ieee-inst Electrical Electronics Engineers IncNew York, 1996)
Model error covariance estimation in particle and ensemble kalman filters using an online expectation–maximization algorithm
(John Wiley & Sons Ltd, 2020-11)
The performance of ensemble-based data assimilation techniques that estimate the state of a dynamical system from partial observations depends crucially on the prescribed uncertainty of the model dynamics and of the ...
Model error estimation using the expectation maximization algorithm and a particle flow filter
(Society of Industrial and Applied Mathematics, 2021-03)
Model error covariances play a central role in the performance of data assimilation methods applied to nonlinear state-space models. However, these covariances are largely unknown in most of the applications. A misspecification ...