径向基函数网络在扩频通信干扰抑制中的应用

Interference Rejection in Spread Spectrum Communication Systems Using Radial Basis Function Network

提出了一种基于径向基函数网络的自适应干扰抑制方法 .与传统的基于反向传播算法的感知器神经网络相比 ,径向基函数网络具有收敛速度快 ,对环境变化不敏感等优点 .计算机仿真结果表明 ,当干扰为窄带信号时 ,利用径向基函数网络可以有效地对干扰进行抑制 .将该方法与基于传统横向滤波器和感知器神经网络的干扰抑制器进行比较 。

A new algorithm for adaptive interference rejection based on radial basis function network was analyzed. Compared with the conventional perception neural network, its convergence rate is fast, and it is robust to the circumstance change. The computer simulation results show that this kind of filter can reject narrow-band interference efficiently and it is superior to other interference filter based on transversal filter or perception neural network.