DocumentCode :
1803675
Title :
New and used bills classification for cepstrum patterns
Author :
Teranishi, Masaru ; Omato, S. ; Kosaka, Toshihisa
Author_Institution :
Dept. of Electr. Eng., Nara Coll. of Technol., Japan
Volume :
6
fYear :
1999
fDate :
36342
Firstpage :
3978
Abstract :
This paper proposes a new method to classify bills into different fatigue levels. Acoustic cepstrum patterns obtained from an acoustic signal generated by a bill 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 bill into three fatigue levels. The experimental results show that the proposed method is useful for classification of fatigue levels of bills, and the LVQ algorithm performs a good classification
Keywords :
acoustic signal processing; bank data processing; learning (artificial intelligence); neural nets; pattern classification; acoustic signal; bank notes; banking machine; cepstrum patterns; competitive neural network; fatigue; learning vector quantization; pattern classification; Banking; Cepstral analysis; Cepstrum; Educational institutions; Electronic mail; Fatigue; Feature extraction; Microphones; Neural networks; Signal generators;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
ISSN :
1098-7576
Print_ISBN :
0-7803-5529-6
Type :
conf
DOI :
10.1109/IJCNN.1999.830794
Filename :
830794
Link To Document :
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