Neural-network-enhanced small low-cost low-power sensor for atmospheric gases

Shannon R. Campbell; Edgar A. Mendoza; Emile Fiesler

doi:10.1117/12.403625

13 October 2000 Neural-network-enhanced small low-cost low-power sensor for atmospheric gases

Shannon R. Campbell, Edgar A. Mendoza, Emile Fiesler

Proceedings Volume 4120, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation III; (2000) https://doi.org/10.1117/12.403625
Event: International Symposium on Optical Science and Technology, 2000, San Diego, CA, United States

Abstract

In this paper, Intelligent Optical Systems, Inc. reports on our progress in using neural network signal processing algorithms for the enhancement of sensor signals from a multigas optical sensor under development for NASA. We found that a 4x8x3 neural network yielded superior results over the last squares (LS), partial least squares (PLS), and principal components regression (PCR) algorithms in estimating oxygen, water vapor, and temperature.

Citation Download Citation

Shannon R. Campbell, Edgar A. Mendoza, and Emile Fiesler "Neural-network-enhanced small low-cost low-power sensor for atmospheric gases", Proc. SPIE 4120, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation III, (13 October 2000); https://doi.org/10.1117/12.403625

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