Tag Archive: Blind Source Separation

Methods for multi-subject electroencephalography – published

My thesis manuscript is available ! The manuscript of my thesis “Methods for Multi-Subject Electroencephalography and application to Brain-Computer Interfaces” has finally be published online (>>download on HAL<<). Of course, not everyone has the time and the motivation to read… (READ MORE)

publication

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Thesis defense – oct. 17, 2018

I am really proud to announce the public defense of my thesis work (provided that I have the approval of the reviewers). Methods for multi-subject electroencephalography and application to brain-computer interfaces Wednesday, October 17th 2018 at 10:00 Location:     Salle Mont-Blanc,… (READ MORE)

News

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Using Riemannian Geometry for Source Separation

Finding hidden variables in data can be challenging. Using Blind Source Separation allows to exact the independent sources in a unsupervised way. However, the methods require usually strong optimization constraints in order to avoid degenerate solutions and/or improve convergence. By… (READ MORE)

Conference, News

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EUSIPCO16: Presenting Composite Approximate Joint Diagonalization

We were in EUSIPCO 2016 conference in Budapest to present our work on Blind Source Separation with Approximate Joint Diagonalization. We shared the idea that using several data models simultaneously can improve the robustness of the data mining. Our composite… (READ MORE)

Code, Conference, News

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