计算机工程与应用Issue(20)：178-182,5.DOI:10.3778/j.issn.1002-8331.1410-0086
分数低阶时频滑动平均模型参数估计
Modeling and parameter estimation based on FLO-TFMA
摘要
Abstract
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Key words
α stable distribution/fractional lower order statistic/moving average model/non-stationary process/time-frequency spectrum estimation分类
信息技术与安全科学引用本文复制引用
汪海滨,龙俊波,查代奉..分数低阶时频滑动平均模型参数估计[J].计算机工程与应用,2015,(20):178-182,5.基金项目
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）。 （）
