Computational model for aircraft's takeoffs pattern recognition

Arturo Rojo Ruiz, Luis P. Sánchez Fernandez, Edgardo Felipe-Riverón, Sergio Suárez Guerra

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Scopus citations

Abstract

This paper presents a novel computational multimodal model designed for pattern recognition of aircrafts' noise in real environments; with an 88.5% of effectiveness, it considers 13 different categories of aircrafts. This method includes measurements of signals of the noise produced during the takeoff at 25,000 samples per second and with a resolution of 24 bits, an spectral analysis made by means of an autoregressive model, an octave analysis, a normalization method created specifically for this work and two feed-forward neural networks. All the signals used for the design and evaluation of the results were obtained by means of field measurements.

Original languageEnglish
Title of host publicationProgress in Pattern Recognition, Image Analysis and Applications - 13th Iberoamerican Congress on Pattern Recognition, CIARP 2008, Proceedings
Pages14-21
Number of pages8
DOIs
StatePublished - 2008
Event13th Iberoamerican Congress on Pattern Recognition, CIARP 2008 - Havana, Cuba
Duration: 9 Sep 200812 Sep 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5197 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th Iberoamerican Congress on Pattern Recognition, CIARP 2008
Country/TerritoryCuba
CityHavana
Period9/09/0812/09/08

Keywords

  • Aircraft
  • Monitoring
  • Noise
  • Pattern
  • Recognition

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