Spectral peak verification and recognition using a multilayered neural network
- 15 December 1990
- journal article
- research article
- Published by American Chemical Society (ACS) in Analytical Chemistry
- Vol. 62 (24) , 2702-2709
- https://doi.org/10.1021/ac00223a011
Abstract
The verification and recognition of peak-shaped signals in analytical data are ubiquitous scientific problems. Experimental data contain overlapping signals and noise, which make sensitive and reliable peak recognition difficult. A peak detection system based on a class of neural networks known as "multilayered perceptrons" has been created. The network was trained and evaluated with use of vapor-phase infrared spectral data. The results of varying the network architecture on system training and prediction performance along with refinement of the form of the input pattern are presented.This publication has 1 reference indexed in Scilit:
- The limitations of models and measurements as revealed through chemometric intercomparisonJournal of Research of the National Bureau of Standards, 1985