Computational Model for Aircraft’s Takeoffs Pattern Recognition

  • Arturo Rojo Ruiz
  • Luis P. Sánchez Fernandez
  • Edgardo Felipe-Riverón
  • Sergio Suárez Guerra
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5197)


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.


aircraft noise pattern recognition monitoring 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Arturo Rojo Ruiz
    • 1
  • Luis P. Sánchez Fernandez
    • 1
  • Edgardo Felipe-Riverón
    • 1
  • Sergio Suárez Guerra
    • 1
  1. 1.Center for Computing Research, National Polytechnic Institute, MexicoMexico CityMexico

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