Title :
A robust neural network classifier for infrasound events using multiple array data
Author :
Ham, Fredric M. ; Park, Sungjin
Author_Institution :
Florida Inst. of Technol., Melbourne, FL, USA
fDate :
6/24/1905 12:00:00 AM
Abstract :
An integral part of the Comprehensive Nuclear-Test-Ban Treaty International Monitoring System is an infrasound monitoring network. This network has the capability to detect and verify infrasonic signals-of-interest, e.g., nuclear explosions, from other unwanted infrasound noise sources. The paper presents classification results of infrasonic events using a robust neural network
Keywords :
acoustic signal processing; backpropagation; feedforward neural nets; filtering theory; multilayer perceptrons; perceptrons; signal classification; Comprehensive Nuclear-Test-Ban Treaty International Monitoring System; classification; infrasound events; infrasound monitoring network; multiple array data; robust neural network classifier; Cepstral analysis; Explosions; Frequency; Geometry; Monitoring; Multilayer perceptrons; Neural networks; Robustness; Sensor arrays; Testing;
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7278-6
DOI :
10.1109/IJCNN.2002.1007556