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自回归谱估计中的谱峰丢失AI 解读

Autoregressive spectral analysis depends on the method used for estimating the autoregressive parameters. It is shown by an asymptotic analysis involving second-order terms that least-squares estimates should be preferred to Yule-Walker estimates, since Yule-Walker estimates may result in loss of spectral peaks and strong bias. The results are confirmed by simulations which include also Burg-type estimates.

自回归谱估计中的谱峰丢失AI 解读

Autoregressive spectral analysis depends on the method used for estimating the autoregressive parameters. It is shown by an asymptotic analysis involving second-order terms that least-squares estimates should be preferred to Yule-Walker estimates, since Yule-Walker estimates may result in loss of spectral peaks and strong bias. The results are confirmed by simulations which include also Burg-type estimates.