Environmental Noise Source Classification Using Neural Networks

Neural networks have been applied to many interesting problems in different areas including noise identification/recognition. With this study, we studied noise classification using artificial neural networks (ANN). Three commonly encountered non-stationary noise sources are chosen to recognize. These are highway, subway and airport. Time-domain based feature parameters are used. While one-phase ANN classifier achieving 54% accuracy, two-phase ANN classifier achieved 83-89% accuracy rates.

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