A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2007; you can also visit the original URL.
The file type is application/pdf
.
Adaptive Modeling and Spectral Estimation of Nonstationary Biomedical Signals Based on Kalman Filtering
2005
IEEE Transactions on Biomedical Engineering
We describe an algorithm to estimate the instantaneous power spectral density (PSD) of nonstationary signals. The algorithm is based on a dual Kalman filter that adaptively generates an estimate of the autoregressive model parameters at each time instant. The algorithm exhibits superior PSD tracking performance in nonstationary signals than classical nonparametric methodologies, and does not assume local stationarity of the data. Furthermore, it provides better time-frequency resolution, and is
doi:10.1109/tbme.2005.851465
pmid:16119245
fatcat:yj73yriqpbgw5ebu6fy3g76zva