DocumentCode
2286313
Title
Classifying emitters in the high frequency range with self-organizing maps
Author
Fanghänel, Karsten ; Köllmann, Kuno ; Raps, Frank ; Zeidler, Hans Christoph
Author_Institution
Univ. der Bundeswehr Hamburg, Germany
Volume
6
fYear
2000
fDate
2000
Firstpage
265
Abstract
In this paper self-organizing maps (SOMs) are proposed for classifying emitters in the high frequency range allowing verification of emitters received by dislocated sensors. With respect to the characteristics of SOMs the classification and verification can be done without any model based knowledge of the different transmission channels. Moreover, both processes seem to be robust against data losses based on a discrete wavelet transform
Keywords
discrete wavelet transforms; learning (artificial intelligence); pattern classification; radio transmitters; self-organising feature maps; signal detection; discrete wavelet transform; learning; pattern classification; self-organizing maps; signal detection; transmission channels; Bandwidth; Data compression; Discrete wavelet transforms; Filters; Frequency; Hafnium; Mirrors; Neural networks; Self organizing feature maps; Signal processing algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
Conference_Location
Como
ISSN
1098-7576
Print_ISBN
0-7695-0619-4
Type
conf
DOI
10.1109/IJCNN.2000.859407
Filename
859407
Link To Document