DocumentCode
2647407
Title
Target identification using neural nets and C4.5
Author
Filippidis
Author_Institution
Inf. Technol. Div., Defence Sci. & Technol. Organ., Salisbury, SA, Australia
fYear
1994
fDate
29 Nov-2 Dec 1994
Firstpage
100
Lastpage
104
Abstract
This paper addresses the application of linear prediction with the backpropagation neural network (BPNN) and C4.5 for distinguishing jet and propeller driven aircraft using Doppler spectra derived from a continuous-wave (CW) coherent (X band) radar. To verify the BPNN´s and C4.5´s classification of the data random noise was added to the Doppler data and results from both techniques compared
Keywords
CW radar; Doppler radar; aircraft; backpropagation; learning (artificial intelligence); military computing; neural nets; radar computing; random noise; C4.5; Doppler spectra; backpropagation neural network; continuous-wave coherent radar; data classification; jet aircraft; linear prediction; neural nets; propeller driven aircraft; random noise; target identification; Airborne radar; Aircraft; Backpropagation; Blades; Doppler radar; Neural networks; Propellers; Radar applications; Radar signal processing; Signal to noise ratio;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Information Systems,1994. Proceedings of the 1994 Second Australian and New Zealand Conference on
Conference_Location
Brisbane, Qld.
Print_ISBN
0-7803-2404-8
Type
conf
DOI
10.1109/ANZIIS.1994.396941
Filename
396941
Link To Document