Difference between revisions of "Exploratory data analysis by genetic feature extraction"

From AIRWiki
Jump to: navigation, search
(New page: {{ProjectProposal |title=Exploratory data analysis by genetic feature extraction |image=Evolve1at300dpi.gif |description=Understanding the waves in EEG signals is an hard task and psicolog...)
 
 
(One intermediate revision by one other user not shown)
Line 6: Line 6:
 
*B. Dal Seno, M. Matteucci, and L. Mainardi. "A genetic algorithm for automatic feature extraction in P300 detection" (http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf)
 
*B. Dal Seno, M. Matteucci, and L. Mainardi. "A genetic algorithm for automatic feature extraction in P300 detection" (http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf)
 
*B. Dal Seno, M. Matteucci, L. Mainardi, F. Piccione, and S. Silvoni. "Single-trial P300 detection in healthy and ALS subjects by means of a genetic algorithm" (http://home.dei.polimi.it/dalseno/papers/2008/grazGa08.pdf)
 
*B. Dal Seno, M. Matteucci, L. Mainardi, F. Piccione, and S. Silvoni. "Single-trial P300 detection in healthy and ALS subjects by means of a genetic algorithm" (http://home.dei.polimi.it/dalseno/papers/2008/grazGa08.pdf)
|tutor=MatteoMatteucci; BernardoDalSeno
+
|tutor=MatteoMatteucci
 
|start=2009/10/01
 
|start=2009/10/01
 
|studmin=1
 
|studmin=1
Line 16: Line 16:
 
|level=Ms
 
|level=Ms
 
|type=Course; Thesis
 
|type=Course; Thesis
|status=Active
+
|status=Closed
 
}}
 
}}

Latest revision as of 16:36, 26 April 2011

Title: Exploratory data analysis by genetic feature extraction
Evolve1at300dpi.gif

Image:Evolve1at300dpi.gif

Description: Understanding the waves in EEG signals is an hard task and psicologists often need automatic tools to perform this task. In this project we are interested in using a genetic algorithm developed for P300 feature extraction in order to extract useful informations from Error Potentials. The project is a collaboration with the psicology department od Padua University.
Tutor: MatteoMatteucci (matteo.matteucci@polimi.it)
Start: 2009/10/01
Students: 1 - 2
CFU: 5 - 20
Research Area: BioSignal Analysis
Research Topic: Brain-Computer Interface
Level: Ms
Type: Course, Thesis
Status: Closed