DocumentCode
1546657
Title
Neural networks applied to continuous range amplitude measurements of small sinusoidal vibrations
Author
Cimponeriu, Andrei
Author_Institution
Dept. of Measurements & Opt. Electron., Timisoara Univ., Romania
Volume
50
Issue
5
fYear
2001
fDate
10/1/2001 12:00:00 AM
Firstpage
1171
Lastpage
1175
Abstract
Neural networks can be used to compute the amplitude of small sinusoidal vibrations measured with the Michelson interferometer. By simulations, the feasibility of the method is proven and the noise behavior is examined. The results are of practical interest: they show that the method is applicable to practical, noisy signals, and the precision can be very good
Keywords
light interferometry; measurement theory; neural nets; noise; vibration measurement; Michelson interferometer; adaptive inverse modeling; continuous range amplitude measurements; neural networks; noise behavior; noisy signals; small sinusoidal vibrations; Adaptive control; Computational modeling; Computer networks; Equations; Inverse problems; Lighting; Mirrors; Neural networks; Photodetectors; Vibration measurement;
fLanguage
English
Journal_Title
Instrumentation and Measurement, IEEE Transactions on
Publisher
ieee
ISSN
0018-9456
Type
jour
DOI
10.1109/19.963179
Filename
963179
Link To Document