DocumentCode
1106810
Title
Finding the poles of the lattice filter
Author
Jones, William B. ; Steinhardt, Allan O.
Author_Institution
University of Colorada, Boulder, CO
Volume
33
Issue
5
fYear
1985
fDate
10/1/1985 12:00:00 AM
Firstpage
1328
Lastpage
1331
Abstract
The lattice filter is often used in spectral analysis problems. Once the reflection coefficients
are found, the task remains of extracting spectral information from them. Frequently this is done by DFT methods. An appealing alternative is to find the poles (modes) of the lattice directly. In this paper, we present an algorithm for computing the poles of the lattice directly from the
. The algorithm is based on the continued fraction expansion representation for the transfer function of the lattice. When applied to a sinusoid in noise, the algorithm found the poles, and hence the sinusoid\´s frequency, in less time than it took using a DFT-based peak detector. Another efficient algorithm is presented which computes the number of poles lying outside the unit circle. It is also based on information obtained directly from the
and employs only integer addition. Finally, it is shown that, by an adaptation of this algorithm, the number of poles lying in an annulus
can be determined.
are found, the task remains of extracting spectral information from them. Frequently this is done by DFT methods. An appealing alternative is to find the poles (modes) of the lattice directly. In this paper, we present an algorithm for computing the poles of the lattice directly from the
. The algorithm is based on the continued fraction expansion representation for the transfer function of the lattice. When applied to a sinusoid in noise, the algorithm found the poles, and hence the sinusoid\´s frequency, in less time than it took using a DFT-based peak detector. Another efficient algorithm is presented which computes the number of poles lying outside the unit circle. It is also based on information obtained directly from the
and employs only integer addition. Finally, it is shown that, by an adaptation of this algorithm, the number of poles lying in an annulus
can be determined.Keywords
Adaptive algorithm; Convergence; Data mining; Filters; Lagrangian functions; Lattices; Narrowband; Reflection; Signal processing algorithms; Symmetric matrices;
fLanguage
English
Journal_Title
Acoustics, Speech and Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
0096-3518
Type
jour
DOI
10.1109/TASSP.1985.1164675
Filename
1164675
Link To Document