JACIII Vol.4 No.1 pp. 18-23
doi: 10.20965/jaciii.2000.p0018


Neuro-Classification of Currency Fatigue Levels Based on Acoustic Cepstrum Patterns

Masaru Teranishi*, sigeru Omatu** and Toshihisa Kosaka***

*Department of Electrical Engineering, Nara National College of Technology 22 Yata-cho, Yamatokoriyama, Nara 639-1080, Japan

**Department of Computer and Systems Sciences, College of Engineering, Osaka Prefecture University Gakuencho, Sakai, Osaka 599-8531, Japan

***Glory Ltd. 1-3-1 Shimoteno, Himeji 670-8567, Japan

October 5, 1998
February 20, 1999
January 20, 2000
Fatigue level classification, Currency classification, LVQ, Acoustic cepstrum patterns
This paper proposes a new method to classify currencies into different fatigue levels. Acoustic cepstrum patterns obtained from an acoustic signal generated by a currency passing through a banking machine are used for classification. The acoustic cepstrum patterns are fed to a competitive neural network with the Learning Vector Quantization (LVQ) algorithm, and classified the currency into three fatigue levels. The experimental results show that the proposed method is useful for classification of fatigue levels of currencies, and the LVQ algorithm performs a good classification.
Cite this article as:
M. Teranishi, S. Omatu, and T. Kosaka, “Neuro-Classification of Currency Fatigue Levels Based on Acoustic Cepstrum Patterns,” J. Adv. Comput. Intell. Intell. Inform., Vol.4 No.1, pp. 18-23, 2000.
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