中文摘要：

基于分数低阶统计量原理提出了α稳定分布下Voherra滤波器的数据块滤波算法。该算法对Volterra滤波器权向量的线性项部分和非线性项部分分别采用不同的收敛因子，克服了传统只采用一个收敛因子的Voherra滤波器算法收敛性能差缺点，利用更多的输入信号和误差信号信息，更好地估计梯度，更精确地调节自适应滤波器权向量，提高了收敛速度。仿真结果验证了该方法的优越性。

英文摘要：

An adaptive data block Volterra filter algorithm is proposed for the α-stable distribution based on the fractional lower order statistics theory. The different convergence factors are used to the linear part and the nonlinear part of the coefficient vectors of Voherra filter to overcome the shortcoming of traditional Volterra filter algorithm that has poor convergence performance by using only a convergence factor. The coefficient vectors are adjusted with more precise gradient estimate by using abundant information of the error and input signals, so that the convergence rate of the proposed algorithm is largely increased. Simulations results verify the superiority of this method.