Abstract
The authors describe a method for estimating accurately the parameters of an autoregressive (AR) process corrupted with high-level white noise. The method is based on phase matching by minimizing the difference between the phase of the all-zero model and that of the maximum-phase signal reconstructed from the power spectrum of the observed signal. The parameters of the AR model are obtained from the finite-length sequence of the estimated all-zero model. Since the phase matching technique is satisfied the conditions for in applying the least-mean-square method, AR parameters are estimated accurately even at the low signal-to-noise ratio.
Original language | English |
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Pages (from-to) | 1381-1384 |
Number of pages | 4 |
Journal | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
Publication status | Published - 1986 Dec 1 |
ASJC Scopus subject areas
- Software
- Signal Processing
- Electrical and Electronic Engineering