電気学会論文誌C(電子・情報・システム部門誌)
Online ISSN : 1348-8155
Print ISSN : 0385-4221
ISSN-L : 0385-4221
紙幣音響データによる新旧紙幣のニューロ識別
姜 東植大松 繁吉岡 理文小坂 利寿
著者情報
ジャーナル フリー

1998 年 118 巻 12 号 p. 1706-1711

詳細
抄録

In this paper, we propose a neuro-classification method of the new and used bills using time-series acoustic data. The technique used here is based on an extension of an adaptive digital filter (ADF) by Widrow and the error back-propagation method. Two-stage ADFs are used to detect the desired acoustic data of bill from noisy input data. In the first stage, superfluous signals are eliminated from input signals and in the next stage, only the desired acoustic data is detected from output signal of the two-stage ADFs. The output signal of two-stage ADFs is transformed into spectral data to produce an input pattern to a neural network (NN). The NN is used to discriminate the new and used bills. It is shown that the experimental result using two-stage ADFs is better than that obtained by using original observation data.

著者関連情報
© 電気学会
前の記事 次の記事
feedback
Top