Classification for target model Based on fuzzy integral function

In order to solve simple classifier that is unable to adapt for the modulation characteristics in a wide range, the signal modulation classification algorithm based on fuzzy integral function has been proposed, which is combining the classification accuracy uncertainty and fuzzy density, using the fusion for multiple classifiers, in order to reduce the uncertainty of single classifier, then to improve the reliability of signal modulation classification. Combining with the Choquet fuzzy integral function, and ensuring the accuracy of the fuzzy density, we use 11 kinds of digital modulation to verify the performance of fuzzy integral function modulation classification algorithm. According to the simulation result, the stability and the classification of the modulation recognition rate is higher than before not less than 99% at the condition of 0dB.