Volume 7, Issue 4 (12-2015)                   IJICTR 2015, 7(4): 1-15 | Back to browse issues page

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Hakimi S, Ebrahimzadeh A. Digital Modulation Classification Using the Bees Algorithm and Probabilistic Neural Network Based on Higher Order Statistics . IJICTR. 2015; 7 (4) :1-15
URL: http://ijict.itrc.ac.ir/article-1-78-en.html
1- Electrical Engineering Department Ferdowsi University Mashhad, Iran
2- Electrical and Computer Engineering Department Babol University of Technology Babol, Iran
Abstract:   (1437 Views)
There has been an increasing demand for automatic classification of digital signal formats during the past decades, which seems to be a continouning trend in future too. Most of the previously proposed classifiers can only classify a few kinds of digital signals and/or a low order of digital signals. In addition, They usually require a high level of Signal to Noise Ratio (SNR). This paper presents a hybrid intelligent system for recognition of digital signal types, including three main modules: a feature extraction module, a classifier module, i.e., a Probabilistic Neural Networks (PNN), and an optimization module. Simulation results validate the high recognition accuracy of the proposed system even at low SNRs.
Full-Text [PDF 1442 kb]   (542 Downloads)    
Type of Study: Research | Subject: Information Technology

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