Model structure selection in convolutive mixtures |
Mads Dyrholm, Scott Makeig, Lars Kai Hansen
|
| Abstract | The CICAAR algorithm (convolutive independent component
analysis with an auto-regressive inverse model) allows
separation of white (i.i.d) source signals from convolutive
mixtures.
We introduce a source color model as a simple
extension to the CICAAR which allows for a more parsimoneous
representation in many practical mixtures. The new filter-CICAAR
allows Bayesian model selection and can help answer questions
like: 'Are we actually dealing with a convolutive mixture?'. We
try to answer this question for EEG data. |
| Keywords | ica convolutive maximum likelihood contextual eeg model selection |
| Type | Conference paper [With referee] |
| Conference | 6th International Conference on Independent Component Analysis and Blind Source Separation |
| Year | 2006 |
| Electronic version(s) | [pdf] |
| BibTeX data | [bibtex] |
| IMM Group(s) | Intelligent Signal Processing |