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
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;
Conference_Titel :
Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
Conference_Location :
Como
Print_ISBN :
0-7695-0619-4
DOI :
10.1109/IJCNN.2000.859407
