Automatic digital modulation recognition using support vector machines and genetic algorithm

Lecture Notes in Computer Science

Volumn 3497, Issue II, 2005, Pages 568-573

  Li, Jie ^a   Peng, Jing ^b   Chu, Heng ^a   Zhu, Weile ^a  

^a UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA   (China)

^b HEBEI UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; GENETIC ALGORITHMS; PROBLEM SOLVING; ROBUSTNESS (CONTROL SYSTEMS); SET THEORY; SIGNAL TO NOISE RATIO; STATISTICAL METHODS; VECTORS;

AUTOMATIC DIGITAL MODULATION RECOGNITION (ADMR); LOCAL OPTIMAL PROBLEMS; SUPPORT VECTOR MACHINES (SVMS);

MODULATION;

EID: 24944473127     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/11427445_93     Document Type: Conference Paper

References (5)

1. Nandi, A.K., Azzouz, E.E.: Modulation Recognition Using Artificial Networks. IEEE Trans. Signal processing, 56 (1997) 165-175
2. Nandi, A.K., Azzouz, E.E.: Algorithms for Automatic Modulation Recognition of Communication Signals. IEEE Trans. Communications, 46 (1998) 431-435
3. Swami, A., Sadler, B.M.: Hierarchical Digital Modulation Classification Using Cumulants. IEEE Trans. Communications, 48 (2000) 416-429
4. Vapnik, V.: An Overview of Statistical Learning Theory. IEEE Trans. Neural Networks, 10 (1999) 988-999
5. Klautau, A., Jevtic, N., Orlitsky, A.: On Nearest-Neighbor Error-Correcting Output Codes with Application to All-Pairs Multiclass Support Vector Machines, Journal of Machine Learning Research, 4 (2003) 1-15