350 rub
Journal Neurocomputers №7 for 2016 г.
Article in number:
Fuzzy decision tree and multilayer neural network for digital modulation recognition
Keywords: modulation modulation recognition cumulants Gaussian noise fuzzy decision tree multilayer neural network
Authors:
Dam Van Nhich - Post-graduate Student, Department IIST FREC, Moscow Institute of Physics and Technology (State University). E-mail: damvan.nhich@gmail.com
Abstract:
The article solves the problem of digital modulation recognition of radio signals based on the using fuzzy decision tree and multilayer neural network. Recognition performed with the basic types of digital modulation 2-PSK, 4-PSK, 8-PSK, 2-FSK, 8-QAM, 16-QAM, 64-QAM. Features for the entrance in the neural network are cumulants. Performance testing methods carried out on one and the same database. The best result shown by using the multilayer neural network.
Pages: 70-73
References

 

  1. Su W., Kosinski J.A. Higher-order blind signal feature separation: An enabling technology for battlefield awareness // U.S. Army Cerdec, Ft Monmouth, NJ 07703.NOV 2006. P. 1-7. PDFURL: ADA481532.
  2. Avedjan EH.D., Dam V.N. K vyboru kumuljantnykh priznakov v zadache raspoznavanija vidov cifrovojj moduljacii radiosignalov // Informatizacija i svjaz. 2015. №4. S. 11-15.
  3. Young A.F. Classification of digital modulation types in multipath environments // Master-s Thesis. Naval Postgraduate School, Monterey, CA 93943-5000, California. 2008. P. 1-65.
  4. Wong M.L.D., Nandi A.K. Automatic digital modulation recognition using artificial neural network and genetic algorithm // Signal Processing 84. 2004. P. 351-365.
  5. Nandi A.K., Azzouz E.E. Modulation recognition using artificial neural networks // Signal Processing 56. 1997. P. 165-175.