Share Email Print

Proceedings Paper

Noise contaminated transmittance
Author(s): Andrew Zardecki; Brian D. McVey; Douglas H. Nelson; Mark J. Schmitt
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

We compare the efficiency of a classifier based on probabilistic neural networks and the general least squares method. Both methods must accommodate noise due to uncertainty in the measured spectrum. The evaluation of both methods is based on a simulated transmittance spectrum, in which the received signal is supplemented by an additive admixture of noise. To obtain a realistic description of the noise mode, we generate several hundred laser pulses for each wavelength under consideration. These pulses have a predetermined correlation matrix for different wavelengths; furthermore, they are composed of three components accounting for the randomness of the observed spectrum. The first component is the correlated 1/f noise; the second component is due to uncorrelated 1/f noise; the third one is the uncorrelated white noise. The probabilistic neural network fails to retrieve the species concentration correctly for large noise levels; on the other hand, its predictions being confined to a fixed number of concentration bins, the network produces relatively small variances. To a large extent, the general least square method avoids the false alarms. It reproduces the average concentrations correctly; however, the concentration variances can be large.

Paper Details

Date Published: 31 October 1997
PDF: 12 pages
Proc. SPIE 3127, Application of Lidar to Current Atmospheric Topics II, (31 October 1997); doi: 10.1117/12.279068
Show Author Affiliations
Andrew Zardecki, Los Alamos National Lab. (United States)
Brian D. McVey, Los Alamos National Lab. (United States)
Douglas H. Nelson, Los Alamos National Lab. (United States)
Mark J. Schmitt, Los Alamos National Lab. (United States)

Published in SPIE Proceedings Vol. 3127:
Application of Lidar to Current Atmospheric Topics II
Arthur J. Sedlacek III; Kenneth W. Fischer, Editor(s)

© SPIE. Terms of Use
Back to Top