可視化情報学会誌
Online ISSN : 1884-037X
Print ISSN : 0916-4731
ISSN-L : 0916-4731
206 ニューラルネットによる学習型流速場測定法
山本 貴幸村田 滋
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1993 年 13 巻 Supplement2 号 p. 103-106

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This paper provides a new Particle Image Velocimetry (PIV) with learning function by Neural Network. This method is based on the Fourier transform method and detects a special shift by using a multiple-layer Neural Network, on purpose to improve the precision of measurement. The network learns the input-output patterns in one-dimensional problem by Error Back Propagation method.
Performance test is carried out in two-dimensional problem and the test results show that the present method induces less errors for the image patterns with velocity fluctuation than the original Fourier transform method.

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