Spectral peak verification and recognition using a multilayered neural network.

Academic Article

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.
  • Authors

  • Wythoff, BJ
  • Levine, SP
  • Tomellini, Sterling
  • Status

    Publication Date

  • December 15, 1990
  • Keywords

  • Artificial Intelligence
  • Chemistry Techniques, Analytical
  • Computer Simulation
  • Humans
  • Models, Theoretical
  • Neurons
  • Digital Object Identifier (doi)

    Pubmed Id

  • 2096735
  • Start Page

  • 2702
  • End Page

  • 2709
  • Volume

  • 62
  • Issue

  • 24