基于RBF神经网络的跳频信号频率预测的研究

RESEARCH ON PREDICTING FREQUENCY-HOPPING SIGNALS BASED ON THE RBF NEURAL NETWORK

提出了一种跳频信号频率预测的解决方案———RBF神经网络.比较了BP神经网络和RBF神经网络在跳频信号频率预测中的性能差异.应用MATLAB针对一伴有随机噪声的信号进行了仿真实验,证明了该理论的可行性与优越性.

A solving plan of prediction of frequency-hopping signals -the RBF neural network is presented. It makes a comparison of the performance differences of the BP neural network and the RBF neural network in predicting frequency-hopping signals. Simulation is carried out to a signal with random noise through the application of MATLAB, which verifies the practicability and the superiority of the theory.