IAS algorithm¶
The Iterative Alternating Sequential (IAS) [Ref1] [Ref2] algorithm is based on an iterative scheme that alternatively updates the dipole moments Q by solving a linear least squares problem using a priorconditioned CGLS algorithm with sutable stopping condition and updating the hyperparameter theta by an explicit formula.
An example of application of IAS to a real dataset can be found in IAS Demo.
Download¶
git clone https://github.com/IAS-code/IAS-MEG.git
- Ref1
D. Calvetti, A. Pascarella, F. Pitolli, E. Somersalo, B. Vantaggi A hierarchical Krylov-Bayes iterative inverse solver for MEG with physiological preconditioning, Inverse Problems, 31 (12), 125005, (2015)
- Ref2
D. Calvetti, A. Pascarella, F. Pitolli, E. Somersalo, B. Vantaggi, Brain Activity Mapping from MEG Data via a Hierarchical Bayesian Algorithm with Automatic Depth Weighting, Brain topography, 1-31, (2018)