分数低阶时频滑动平均模型参数估计  

Modeling and parameter estimation based on FLO-TFMA

作　　者：汪海滨[1] 龙俊波[2] 查代奉[3] 

机构地区：[1]九江学院信息科学与技术学院,江西九江332005 [2]九江学院电子工程学院,江西九江332005 [3]九江学院理学院,江西九江332005

出　　处：《计算机工程与应用》2015年第20期178-182,共5页Computer Engineering and Applications

基　　金：国家自然科学基金(No.61261046);江西省自然科学基金(No.20142BAB207006);江西省教育厅青年科技基金(No.GJJ11621;No.GJJ11245;No.GJJ11244;No.GJJ14739;No.GJJ14721);九江学院科技项目(No.2013KJ01;No.2013KJ02)

摘　　要：针对稳定分布环境下非平稳过程分析方法时频滑动平均(TFMA)模型算法的退化,引入分数低阶统计量共变,提出了一种改进的分数低阶时频时频滑动平均(FLO-TFMA)模型算法。推导了FLO-TFMA模型的参数求解过程,给出了基于FLO-TFMA模型的时频谱估计。通过在稳定分布环境下对TFMA模型算法和所提出的FLO-TFMA模型算法的参数估计均方误差(MSE)比较和时频谱估计比较,仿真结果表明,FLO-TFMA模型算法的参数估计精度优于TFMA模型算法,TFMA模型时频谱估计完全失效,而FLO-TFMA模型时频谱算法能较好地进行时频谱估计。The Time-Frequency Moving Average（TFMA）model algorithm which is a method of non-stationary signal processing degenerate under α stable distribution environment, the fractional lower order statistics covariance is intro-duced and the improved Fractional Lower Order Time-Frequency Moving Average algorithm（FLO-TFMA）model algo-rithm is proposed. The parameters estimation of FLO-TFMA model is developed and time-frequency spectrum estimation is given based on the FLO-TFMA model. By comparing the Mean Square Error（MSE）of parameter estimation and spec-trum estimation of the TFMA model algorithm and the proposed FLO-TFMA model algorithm under α stable distribution environment condition, simulations show that the parameters estimation precision of the FLO-TFMA model algorithm is better than TFMA model algorithm, the TFMA model spectrum estimation can not work, and FLO-TFMA model algo-rithm provides better performance of time-frequency spectrum.

关 键 词：稳定分布 分数低阶统计量 滑动平均模型 非平稳过程 时频谱估计 

分 类 号：TN911.72[电子电信—通信与信息系统]