Title :
A Research on Automatic Modulation Recognition with the Combination of the Rough Sets and Neural Network
Author :
Wang, Hua-Kui ; Zhang, Bin ; Wu, Juan-Ping ; Han, Ying-Zheng ; Wu, Xiao-Wei ; Jia, Ruo-Si
Author_Institution :
Coll. of Inf. Eng., Taiyuan Univ. of Technol., Taiyuan, China
Abstract :
Automatic modulation recognition of modulation signals is the key problem in non-cooperative communication systems. The method which combines the rough set theory and the neural network is designed for identifying the six modulation types based on the research on the feature set of digital modulation recognition. Simulation results show that the new method simplifies the structure of neural networks and decreases the training time without reducing the recognition rate.
Keywords :
modulation; neural nets; rough set theory; signal detection; automatic modulation recognition; digital modulation recognition; modulation signals; neural network; noncooperative communication system; rough set combination; rough set theory; Artificial neural networks; Digital modulation; Feature extraction; Rough sets; Training; automatic modulation recognition; neural network; rough set;
Conference_Titel :
Pervasive Computing Signal Processing and Applications (PCSPA), 2010 First International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-8043-2
Electronic_ISBN :
978-0-7695-4180-8
DOI :
10.1109/PCSPA.2010.201
