Abstract
This paper proposes a method to classify new and used bills using the acoustic cepstrum pattern by neural networks. The proposed method deals with an acoustic signal which has been generated by the bill passing through a banking machine. By using an acoustic cepstrum pattern, the rough structure of the acoustic spectrum can be represented as the cepstrum with a smaller pattern size than the spectrum. The proposed method employs a neural network as the classifier. Two different types of the neural network, one is the three layered perceptron and the other is the competitive neural network, are used to evaluate which type is more suitable for classification of the cepstrum pattern. The experimental results show the effectiveness of the proposed method, and that the competitive neural network yields better classification performance than the three-layered perceptron.
