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Linear and Neural Network Models for Predicting Human Signal Detection Performance From Event-Related Potentials: A Comparison of the Wavelet Transform With Other Feature Extraction Methods (1993)
| Venue: | Society for Computer Simulation |
| Citations: | 3 - 1 self |
BibTeX
@INPROCEEDINGS{Trejo93linearand,
author = {Leonard J. Trejo and Mark J. Shensa},
title = {Linear and Neural Network Models for Predicting Human Signal Detection Performance From Event-Related Potentials: A Comparison of the Wavelet Transform With Other Feature Extraction Methods},
booktitle = {Society for Computer Simulation},
year = {1993},
pages = {153--161}
}
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Abstract
This report describes the development and evaluation of mathematical models for predicting human performance from discrete wavelet transforms (DWT) of event-related potentials (ERP) elicited by task-relevant stimuli. The DWT was compared to principal components analysis (PCA) for representation of ERPs in linear regression and neural network models developed to predict a composite measure of human signal detection performance. Linear regression models based on coefficients of the decimated DWT predicted signal detection performance with half as many free parameters as comparable models based on PCA scores and were relatively more resistant to model degradation due to over-fitting. Feed-forward neural networks were trained using the backpropagation algorithm to predict signal detection performance based on raw ERPs, PCA scores, or high-power coefficients of the DWT. Neural networks based on highpower DWT coefficients trained with fewer iterations, generalized to new data better, and wer...
Keyphrases
human signal detection performance neural network model event-related potential feature extraction method wavelet transform signal detection performance comparable model pca score feed-forward neural network raw erps new data principal component analysis neural network human performance linear regression model dwt coefficient backpropagation algorithm many free parameter discrete wavelet transforms task-relevant stimulus mathematical model composite measure linear regression decimated dwt
