Modulation mode Recognition based on multi-class classification of support vector machine
Qian Ren, Guangmin Sun, Yuanyuan Zhang · Advances in intelligent systems research/Advances in Intelligent Systems Research · 2013
An analog and digital modulation recognition method based on support vector machine (SVM) is proposed.A multi-class classifier is designed through the reasonable use of SVM multi-class classification method.A comparison for the performances of one-against-all (OAA), one-against-one (OAO) and binary tree (BT) with the different kernels of SVM is made.Experimental results show that the Gaussian radial basis function (GRBF) kernel has better performance than others.It can be seen from the simulation result that the proposed method is correct and efficient.The scheme can achieve 93% recognition accuracy at low levels of SNR.