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Proceedings Paper

Sensor calibration methods: performance study
Author(s): Oren Masory; Arturo Luis Aguirre
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Paper Abstract

The calibration of a 2-D displacement sensor that suffers from nonlinearities and cross talking using an Artificial Neural Networks (ANN) is described. The ANN is used as a Pattern Associator that is trained to perform the mapping between the sensor''s readings and the actual sensed properties. For comparison purposes a few methods were explored: 1 ) A three-layer ANN with a different number of hidden units trained by the Back Propagation (BP) method 2) Cerebellar Model Arithmetic Computer (CMAC) with a fixed number of quantizing functions and 3) Polynomial curve fitting technique. The results of the calibration procedure and recommendations are discussed. 2.

Paper Details

Date Published: 1 August 1990
PDF: 12 pages
Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); doi: 10.1117/12.21200
Show Author Affiliations
Oren Masory, Florida Atlantic Univ. (United States)
Arturo Luis Aguirre, Florida Atlantic Univ. (United States)

Published in SPIE Proceedings Vol. 1294:
Applications of Artificial Neural Networks
Steven K. Rogers, Editor(s)

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