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Proceedings Paper

Highly precise signal-subdivision method of grating based on BP neural network
Author(s): Wei-Fang Chen; Hao-Jie Xia; Shen-Wang Lin; Hsueh-Cheng Liao
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Paper Abstract

This paper has researched signal processing methods of grating measurement system, and has come out a method to subdivide grating signals based on BP neural network. This measuring method focuses on the special property of the obtained grating signal. The method also decreases the precision requirement of the signal. When the measuring system changes, subdivision models can be altered automatically by software. BP neural networks can subdivide grating signals with few sampling points but high magnitude. This subdivide-method combines software and hardware, has simple structure, does not require complex circuit, and has a strong adaptive system.

Paper Details

Date Published: 31 December 2008
PDF: 6 pages
Proc. SPIE 7130, Fourth International Symposium on Precision Mechanical Measurements, 71304P (31 December 2008); doi: 10.1117/12.819729
Show Author Affiliations
Wei-Fang Chen, Far East Univ. (Taiwan)
Hao-Jie Xia, Hefei Univ. of Technology (China)
Shen-Wang Lin, Far East Univ. (Taiwan)
Hsueh-Cheng Liao, National Taiwan Industrial School (Taiwan)

Published in SPIE Proceedings Vol. 7130:
Fourth International Symposium on Precision Mechanical Measurements
Yetai Fei; Kuang-Chao Fan; Rongsheng Lu, Editor(s)

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