Neural Networks for Vehicle Recognition
نویسندگان
چکیده
In this contribution we describe a neural approach to classify vehicles based on sound emitted by them. Engines and the carriageable devices are the sources of signal. The used methodology doesn't require the detailed analysis which part of object is responsible for the components of signal. The sound is preprocessed using wavelet method to obtain feature vectors to be used by a neural classifier. We test and compare two different neural networks multilayer perceptron (MLP) and probabilistic neural network (PNN) based on gaussian mixture as neural recognition devices. Results of classification of various military vehicles are the subject of conclusions. The described methods can be used as the basis for inteligent robots.
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تاریخ انتشار 2007