Title :
Lag-windowing and multiple-data-windowing are roughly equivalent for smooth spectrum estimation
Author :
Scharf, Louis L. ; Mullis, C.T.
fDate :
3/1/1999 12:00:00 AM
Abstract :
There is no fundamental difference between lag-windowing a correlation sequence and multiple-windowing a data sequence when the objective is to reduce the mean-squared error of a spectrum estimator. By analyzing the approximate low-rank factorization of a bandlimiting Toeplitz operator, we find that lag-windowed (or spectrally smoothed) spectrum estimators have multiple-data-windowed implementations. This makes the Blackman-Tukey-Grenander-Rosenblatt spectrogram equivalent to the Thomson spectrum estimator (and vice-versa), meaning BTGR spectrograms may be implemented in a multichannel filterbank version of the Thomson estimator.
Keywords :
Toeplitz matrices; channel bank filters; estimation theory; low-pass filters; matrix decomposition; mean square error methods; sequences; spectral analysis; BTGR spectrograms; Blackman-Tukey-Grenander-Rosenblatt spectrogram; Thomson estimator; Thomson spectrum estimator; approximate low-rank factorization; bandlimiting Toeplitz operator; correlation sequence; data sequence; lag-windowing; mean-squared error; multichannel filterbank; multiple-data-windowed implementations; multiple-data-windowing; smooth spectrum estimation; spectrum estimator; Autocorrelation; Eigenvalues and eigenfunctions; Filter bank; Kernel; Random processes; Spectral analysis; Spectrogram;
Journal_Title :
Signal Processing, IEEE Transactions on