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Full-Text Articles in Computational Engineering
Electroencephalogram Artifact Removal Using A Wavelet Neural Network, Hoang-Anh T. Nguyen
Electroencephalogram Artifact Removal Using A Wavelet Neural Network, Hoang-Anh T. Nguyen
Electrical & Computer Engineering Theses & Dissertations
A wavelet neural network (WNN) technique rs developed for electroencephalogram (EEG) artifact removal without electrooculographic (EOG) recordings. The algorithm combines the universal approximation characteristics of neural networks and the time/frequency property of wavelet, where the neural network was trained on a simulated dataset with known ground truths. The contribution of this thesis is two-fold. First, many EEG artifact removal algorithms, including regression based methods, require reference EOG signals, which are not always available. To remove EEG ai1ifacts, a WNN tries to learn the characteristics of the artifacts first and does not need reference EOG signals once trained. Second, WNNs are …
Pretty Lights, Nicholas (Nick) Delmas, Matthew (Matt) Maniaci
Pretty Lights, Nicholas (Nick) Delmas, Matthew (Matt) Maniaci
Computer Engineering
Digital media players often include a visualization component that allows a user to watch a visualization synchronized to their music or videos. This project uses the visualization plugin API of an existing media playback program (WinAmp) but it displays its visuals using physical LED lights. Instead of outputting visuals to the computer screen, data is sent over USB to a micro controller that runs the LED lights. This project aims to give users a more visceral visual experience than traditional visualizations on the computer screen.