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Method of Modulation Recognition Based on Combination Algorithm of K-Means Clustering and Grading Training SVM 被引量:7

Method of Modulation Recognition Based on Combination Algorithm of K-Means Clustering and Grading Training SVM
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摘要 For the existing support vector machine, when recognizing more questions, the shortcomings of high computational complexity and low recognition rate under the low SNR are emerged. The characteristic parameter of the signal is extracted and optimized by using a clustering algorithm, support vector machine is trained by grading algorithm so as to enhance the rate of convergence, improve the performance of recognition under the low SNR and realize modulation recognition of the signal based on the modulation system of the constellation diagram in this paper. Simulation results show that the average recognition rate based on this algorithm is enhanced over 30% compared with methods that adopting clustering algorithm or support vector machine respectively under the low SNR. The average recognition rate can reach 90% when the SNR is 5 dB, and the method is easy to be achieved so that it has broad application prospect in the modulating recognition. For the existing support vector machine, when recognizing more questions, the shortcomings of high computational complexity and low recognition rate under the low SNR are emerged. The characteristic parameter of the signal is extracted and optimized by using a clustering algorithm, support vector machine is trained by grading algorithm so as to enhance the rate of convergence, improve the performance of recognition under the low SNR and realize modulation recognition of the signal based on the modulation system of the constellation diagram in this paper. Simulation results show that the average recognition rate based on this algorithm is enhanced over 30% compared with methods that adopting clustering algorithm or support vector machine respectively under the low SNR. The average recognition rate can reach 90% when the SNR is 5 dB, and the method is easy to be achieved so that it has broad application prospect in the modulating recognition.
出处 《China Communications》 SCIE CSCD 2018年第12期55-63,共9页 中国通信(英文版)
基金 supported in part by the National Natural Science Foundation of China under Grand No.61871129 and No.61301179 Projects of Science and Technology Plan Guangdong Province under Grand No.2014A010101284
关键词 CLUSTERING ALGORITHM FEATURE extraction GRADING ALGORITHM support VECTOR machine MODULATION recognition clustering algorithm feature extraction grading algorithm support vector machine modulation recognition
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