TY - JOUR
T1 - Reconocimiento de clases de aeronaves con base en patrones del ruido en el despegue
AU - Sánchez Pérez, Luis Alejandro
AU - Sánchez-Fernández, Luis Pastor
AU - Suarez-Guerra, Sergio
PY - 2016
Y1 - 2016
N2 - In this work the aircraft class recognition of based on take-off noise patterns is examined. Signal segmentation in time is analyzed as well as using a MLP neural network as the classifier for each segment. Also, several algorithms for decision by committee in order to aggregate the multiple parallel outputs of the classifiers are examined along with feature extraction and selection based on spectrum analysis of the aircraft noise. Also, a method for georeferenced estimation of the take-off flight path based only on the noise signal is explored. The methodology and results are sustained in the current literature.
AB - In this work the aircraft class recognition of based on take-off noise patterns is examined. Signal segmentation in time is analyzed as well as using a MLP neural network as the classifier for each segment. Also, several algorithms for decision by committee in order to aggregate the multiple parallel outputs of the classifiers are examined along with feature extraction and selection based on spectrum analysis of the aircraft noise. Also, a method for georeferenced estimation of the take-off flight path based only on the noise signal is explored. The methodology and results are sustained in the current literature.
KW - Airport noise, aircraft class recognition, signal segmentation
KW - Neural network
UR - http://www.scopus.com/inward/record.url?scp=85007337244&partnerID=8YFLogxK
U2 - 10.13053/CyS-20-4-2429
DO - 10.13053/CyS-20-4-2429
M3 - Artículo
SN - 1405-5546
VL - 20
SP - 799
EP - 825
JO - Computacion y Sistemas
JF - Computacion y Sistemas
IS - 4
ER -