Spectral estimation of segmented signals with extrapolation

Ok-Hyeon Kim, A. Poularikas
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引用次数: 3

Abstract

A method is proposed to find the power spectrum of signals with missing observations. The missing observations were first found by the linear prediction method and then an AR model was assumed and the Burg algorithm was used to estimate the spectrum for each segment of the signal. The coefficients found by Burg's method were updated every time the next value of the missing signal was predicted. After the missing observations were found then the power spectra were estimated using the following three different approaches: (a) averaging in the time domain, (b) averaging the spectra of each segment, and (c) averaging the coefficients of the AR model.
外推分割信号的频谱估计
提出了一种寻找缺失观测信号功率谱的方法。首先通过线性预测方法找到缺失观测值,然后假设AR模型,并使用Burg算法估计信号各段的频谱。Burg方法得到的系数在每次预测缺失信号的下一个值时进行更新。在发现缺失观测值后,使用以下三种不同的方法估计功率谱:(a)时域平均,(b)每段光谱平均,(c)平均AR模型系数。
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