中文说明：
RBF为径向基函数，RBF网络把网络看作对未知函数的逼近器。输入信号为正弦信号u(k)=0.35sin(3*pi*t)，采用时间为0.001s,网络隐层神经元个数取m=4，网络结构为输入层2-隐层4-输出1，网络的出事全职取随机值，高斯函数的初始值取Cj=[0.65,0.65]T,B=[1.35,1.35,1.35,1.35]T,网络的学习参数取a=0.07,n=0.9。
English Description：
RBF is a radial basis function. RBF network regards the network as an approximator of unknown function. The input signal is sinusoidal signal U (k) = 0.35sin (3 * pi * t), the adoption time is 0.001s, the number of hidden layer neurons of the network is m = 4, the network structure is input layer 2-hidden layer 4-output 1, the accident time of the network is random value, the initial value of Gaussian function is CJ = [0.65,0.65] t, B = [1.35,1.35,1.35,1.35] t, the learning parameters of the network are a = 0.07, n = 0.9.