Wavelet-based hybrid neurosystem for feature extractions, characterizations and signal classifications

This paper presents an efficient method for signal classification from a system of multiple artificial neural networks (ANN) using wavelets. The method performs feature extraction via the wavelet transform of the underlying signal and presents the resulting coefficients to a hybrid neural network for classification. The hybrid network consists of three single neural networks; two of the networks are provided with magnitude and location information of the coefficients, and are trained with self-organizing rules. Their outputs are then presented to the third network for pattern recognition and classification. Experimental results illustrating concept feasibility for acoustic signal classifications are included.