Frequency Hopping Prediction Based On Multi-Kernel Svm

The chaotic frequency hopping sequences possesses short-term predictability. Via the phase space reconstruction approach, we can get chaos attractors, and the problem of series prediction can be transformed into the regression problem of the chaotic attractors. This paper uses SVR method to deal with the prediction of frequency hopping sequences. After analyzing the characteristics of existing kernel functions, we produce a new multi-kernel function, which is used for the prediction of frequency hopping sequences. Experiments show the fine performances of our methods.