Computational model for aircraft's takeoffs pattern recognition

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

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

11 Citas (Scopus)

Resumen

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.

Idioma originalInglés
Título de la publicación alojadaProgress in Pattern Recognition, Image Analysis and Applications - 13th Iberoamerican Congress on Pattern Recognition, CIARP 2008, Proceedings
Páginas14-21
Número de páginas8
DOI
EstadoPublicada - 2008
Evento13th Iberoamerican Congress on Pattern Recognition, CIARP 2008 - Havana, Cuba
Duración: 9 sep. 200812 sep. 2008

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen5197 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia13th Iberoamerican Congress on Pattern Recognition, CIARP 2008
País/TerritorioCuba
CiudadHavana
Período9/09/0812/09/08

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