DocumentCode :
1802735
Title :
An infrasonic event neural network classifier
Author :
Ham, Fredric M. ; Leeney, Thomas A. ; Canady, Heather M. ; Wheeler, Joseph C.
Author_Institution :
Electr. Eng. Program, Florida Inst. of Technol., Melbourne, FL, USA
Volume :
6
fYear :
1999
fDate :
36342
Firstpage :
3768
Abstract :
An integral part of the Comprehensive Nuclear Test Ban Treaty International Monitoring System is an infrasonic monitoring network that is capable of detecting and verifying nuclear explosions. Reliable detection of such events must be made from data that may contain other sources of infrasonic phenomena, such as volcano eruptions, mountain associated waves (MAW), gravity waves, and microbaroms, to name a few. Infrasonic waves are sub-audible acoustic waves typically in the frequency range 0.01<f<10 Hz. In the interest of working toward the development of a robust neural network discriminator for the IMS, for defecting and classifying nuclear explosions, we have studied the feasibility of discriminating between the infrasonic signatures of volcano activity (MAW), and internal atmospheric gravity waves using a neural discriminator
Keywords :
acoustic signal processing; acoustic waves; military computing; neural nets; nuclear explosions; pattern classification; weapons; 0.01 to 10 Hz; Comprehensive Nuclear Test Ban Treaty; International Monitoring System; gravity waves; infrasonic monitoring network; infrasonic waves; mountain associated waves; neural discriminator; neural network; nuclear explosions; pattern classification; volcano activity; Acoustic signal detection; Acoustic waves; Event detection; Explosions; Frequency; Gravity; Monitoring; Neural networks; System testing; Volcanoes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
ISSN :
1098-7576
Print_ISBN :
0-7803-5529-6
Type :
conf
DOI :
10.1109/IJCNN.1999.830753
Filename :
830753
Link To Document :
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