OpenMEEG: Hands-on tutorial
ثبت نشده
چکیده
By default matrices and vectors are stored on disk using a MATLAB file format. Symmetric matrices which are not directly representable in the MATLAB format are represented as a MATLAB struct. Other vector/matrices file formats are also supported. Forcing a specific file format is achieved by specifying the proper file extension. Matlab extension is .mat. Other useful file formats are ASCII (extension .txt) which generates human readable files, BrainVisa texture file format (extension .tex) and OpenMEEG’s own binary file format (extension .bin) which is available solely for backward compatibility and should be considered as deprecated (as it is subsumed by the MATLAB file format).
منابع مشابه
Forward Field Computation with OpenMEEG
To recover the sources giving rise to electro- and magnetoencephalography in individual measurements, realistic physiological modeling is required, and accurate numerical solutions must be computed. We present OpenMEEG, which solves the electromagnetic forward problem in the quasistatic regime, for head models with piecewise constant conductivity. The core of OpenMEEG consists of the symmetric ...
متن کاملOpenMEEG: opensource software for quasistatic bioelectromagnetics
BACKGROUND Interpreting and controlling bioelectromagnetic phenomena require realistic physiological models and accurate numerical solvers. A semi-realistic model often used in practise is the piecewise constant conductivity model, for which only the interfaces have to be meshed. This simplified model makes it possible to use Boundary Element Methods. Unfortunately, most Boundary Element soluti...
متن کاملBenjamin Hofner , Andreas Mayr , Nikolay Robinzonov , Matthias Schmid Model - based Boosting in R : A Hands - on Tutorial Using the R Package mboost
We provide a detailed hands-on tutorial for the R add-on package mboost. The package implements boosting for optimizing general risk functions utilizing component-wise (penalized) least squares estimates as base-learners for fitting various kinds of generalized linear and generalized additive models to potentially high-dimensional data. We give a theoretical background and demonstrate how mboos...
متن کاملModel-based Boosting in R: A Hands-on Tutorial Using the R Package mboost
We provide a detailed hands-on tutorial for the R add-on package mboost. The package implements boosting for optimizing general risk functions utilizing component-wise (penalized) least squares estimates as base-learners for fitting various kinds of generalized linear and generalized additive models to potentially high-dimensional data. We give a theoretical background and demonstrate how mboos...
متن کاملUsing Machine Learning for Exploratory Data Analysis
This tutorial will introduce attendees to fundamental concepts in the clustering and dimensionality reduction fields of unsupervised machine learning. Attendees will learn about the assumptions algorithms make and how those assumptions can cause the algorithms to be more or less suited to particular datasets. Hands-on interaction with machine learning algorithms on real and synthetic data are a...
متن کامل