Acoustic Feature Extraction for a Neural Network Classifier.
Mark C. Wellman, Nassy Srour, David B. Hillis · 1997
Abstract : Artificial neural networks can perform reliable classification of ground vehicles based solely on their acoustic signatures, if robust features can be identified. We present feature extraction and classification results using simple power spectrum estimates, harmonic line association, and principal component analysis. Algorithm implementation and performance analysis of each feature extraction method are discussed. Also given are preliminary evaluation results of a VLSI (very-large-scale integration) device dedicated to neural network implementation.