Title :
Signal understanding: an artificial intelligence approach to modulation classification
Author :
Whelchel, J.E. ; McNeill, D.L. ; Hughes, R.D. ; Loos, M.M.
Author_Institution :
E-Syst. Melpar Div., Falls Church, VA, USA
Abstract :
A signal understanding system being developed and evaluated by means of simulation is described. The system consists of a new type of generalized demodulation/feature extraction section followed by a statistical moment generator, and then by a pattern classifier. The classifier is based on neural network topology. An algorithmic maximum-likelihood (ML) pattern classifier was also used to evaluate the performance of the neural network. Signal generation, feature extraction, and the ML classifier were implemented using VAX/VMS Fortran. The neural network was implemented on a PC-based Hecht-Neilson ANZA neurocomputer
Keywords :
computerised pattern recognition; computerised signal processing; neural nets; ML classifier; PC-based Hecht-Neilson ANZA neurocomputer; VAX/VMS Fortran; algorithmic maximum-likelihood; artificial intelligence; feature extraction; modulation classification; network training; neural network topology; pattern classifier; signal understanding system; statistical moment generator; Artificial intelligence; Demodulation; Feature extraction; Filtering; Frequency estimation; Maximum likelihood estimation; Neural networks; Phase estimation; Quadrature phase shift keying; Surveillance;
Conference_Titel :
Tools for Artificial Intelligence, 1989. Architectures, Languages and Algorithms, IEEE International Workshop on
Conference_Location :
Fairfax, VA
Print_ISBN :
0-8186-1984-8
DOI :
10.1109/TAI.1989.65325
