NDLI: Modulation Recognition Based on Combined Feature Parameter and Modified Probabilistic Neural Network

Content Provider	IEEE Xplore Digital Library
Author	Yulong Gao Zhongzhao Zhang
Copyright Year	2006
Description	Author affiliation: Commun. Res. Center, Harbin Inst. of Technol. (Yulong Gao; Zhongzhao Zhang)
Abstract	Criterions that weigh the performance of modulation recognition algorithm were presented according to the modulation recognition process and purpose. In terms of these criterions, the combined feature parameters were extracted exploiting the propriety of the cyclic spectral correlation algorithm, these parameters consisted of parameters of cyclic spectral correlation and frequency field. The modified probabilistic neural network was used as a classifier algorithm. The modulation types can be identified dynamically availing oneself of the presented combined feature parameters and the classifier algorithm. The new algorithm presented in this paper can improve the recognition performance and expand the range of recognition, but it does not increase the computational complexity simultaneously. The simulation results obtained by Monte-Carlo method proved these
Starting Page	2954
Ending Page	2958
File Size	231768
Page Count	5
File Format	PDF
ISBN	1424403324
DOI	10.1109/WCICA.2006.1712907
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Electronic mail Feature extraction Frequency Computational modeling Guidelines Intelligent control Automation modulation recognition guideline cyclic spectral correlation modulation recognition probabilistic neural network detection probability
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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