Non-stationary magnetoencephalography by Bayesian filtering of dipole models

DOI10.1088/0266-5611/19/5/304zbMath1046.92034OpenAlexW2027002914MaRDI QIDQ4460645

Erkki Somersalo, Arto Voutilainen, Jari P. Kaipio

Publication date: 18 May 2004

Published in: Inverse Problems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1088/0266-5611/19/5/304

zbMATH Keywords

Markov processBayesian filteringdynamic dipole models

Mathematics Subject Classification ID

Bayesian inference (62F15) Biological applications of optics and electromagnetic theory (78A70) Biomedical imaging and signal processing (92C55)

Related Items (7)

Bayesian Analysis of ODEs: Solver Optimal Accuracy and Bayes Factors ⋮ A statistical approach to the inverse problem in magnetoencephalography ⋮ Particle filters for magnetoencephalography ⋮ Dynamic filtering of static dipoles in magnetoencephalography ⋮ Inverse problems in biomedical imaging: modeling and methods of solution ⋮ GARCH modelling of covariance in dynamical estimation of inverse solutions ⋮ Sequential Monte Carlo estimation of aerosol size distributions

This page was built for publication: Non-stationary magnetoencephalography by Bayesian filtering of dipole models