Chandan Gope, a Ph.D. graduate student in the Electrical Engineering Department in the Erik Jonsson School of Engineering and Computer Science at The University of Texas at Dallas (UTD), won one of the four “Best Student Poster Paper” awards presented at the 2005 International Joint Conference on Neural Networks held earlier this month in Montreal.
Co-authors of the paper with Gope were Dr. Nasser Kehtarnavaz, a professor of electrical engineering in the Jonsson School, and Dinesh Nair, principal software architect at National Instruments. The paper was written as part of the National Instruments-sponsored research and teaching program in signal and image processing at UTD.
More than 330 poster papers and 230 oral papers were presented at the conference, which was jointly organized by the International Neural Network Society and the Institute of Electrical and Electronics Engineers (IEEE) Computational Intelligence Society.
The Gope-Kehtarnavaz-Nair paper discusses a software system designed to more effectively classify EEG (electroencephalography) signals based on independent component analysis, time-frequency features and neural network classification. It also utilizes the NI LabVIEW graphical programming environment to achieve an interactive software design.