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Visual Inference ProgrammingThe goal of visual inference programming is to develop a software framework data analysis and to provide machine learning algorithms for inter-active data exploration and visualization. The topics include: 1) Intelligent Data Understanding (IDU) framework; 2) Challenge problems; 3) What's new here; 4) Framework features; 5) Wiring diagram; 6) Generated script; 7) Results of script; 8) Initial algorithms; 9) Independent Component Analysis for instrument diagnosis; 10) Output sensory mapping virtual joystick; 11) Output sensory mapping typing; 12) Closed-loop feedback mu-rhythm control; 13) Closed-loop training; 14) Data sources; and 15) Algorithms. This paper is in viewgraph form.
Document ID
20030014484
Acquisition Source
Ames Research Center
Document Type
Other
Authors
Wheeler, Kevin
(NASA Ames Research Center Moffett Field, CA United States)
Timucin, Dogan
(NASA Ames Research Center Moffett Field, CA United States)
Rabbette, Maura
(Bay Area Environmental Research Inst. CA United States)
Curry, Charles
(QSS Group, Inc. United States)
Allan, Mark
(QSS Group, Inc. United States)
Lvov, Nikolay
(QSS Group, Inc. United States)
Clanton, Sam
(QSS Group, Inc. United States)
Pilewskie, Peter
(NASA Ames Research Center Moffett Field, CA United States)
Date Acquired
August 21, 2013
Publication Date
June 13, 2002
Subject Category
Computer Programming And Software
Meeting Information
Meeting: National Research Council (NRC) Demo Presentations
Country: Unknown
Start Date: June 13, 2002
Funding Number(s)
PROJECT: RTOP 704-00-00
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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