1 August 1990 Sensor calibration methods: performance study
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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.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Oren Masory, Oren Masory, Arturo Luis Aguirre, Arturo Luis Aguirre, "Sensor calibration methods: performance study", Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); doi: 10.1117/12.21200; https://doi.org/10.1117/12.21200
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