DocumentCode :
527297
Title :
Modulation classification using genetic algorithm and radial basis neural network based on the HOS
Author :
Ebrahimzadeh, Ataollah ; Ghazalian, Reza
Author_Institution :
Fac. of Electr. & Comput. Eng., Babol Univ. of Technol., Babol, Iran
fYear :
2010
fDate :
16-18 Aug. 2010
Firstpage :
375
Lastpage :
378
Abstract :
This paper presents a hybrid intelligent system that automatically recognizes a variety of digital communication signals. The hybrid system includes three main modules: feature extraction module, classifier module and optimization module. In this feature extraction module, a suitable set of the higher order moments up to eighth and higher order cumulants up to eighth are proposed as the prominent characteristic of signals. In the optimization module it is optimized the recognizer design by genetic algorithm for selection the best features that are fed to the classifier. Simulation results show that the proposed technique has very high recognition accuracy with six features selected by optimizer.
Keywords :
genetic algorithms; modulation; radial basis function networks; signal classification; telecommunication signalling; digital communication signal; feature extraction module; genetic algorithm; hybrid intelligent system; modulation classification; optimization module; radial basis neural network; Bioinformatics; Feature extraction; Genomics; Modulation; Signal to noise ratio; Testing; communication signals recognition; genetic algorithm; higher order cumulants; higher order moments; radial basis neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Content, Multimedia Technology and its Applications (IDC), 2010 6th International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4244-7607-7
Electronic_ISBN :
978-8-9886-7827-5
Type :
conf
Filename :
5568619
Link To Document :
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