ALGORITHMS FOR LEAST-SQUARES LINEAR PREDICTION AND MAXIMUM ENTROPY SPECTRAL ANALYSIS

Authors
  1. Barrodale, I.
  2. Erickson, R.E.
Corporate Authors
Victoria Univ, Victoria BC (CAN) Dept of Mathematics;Defence Research Establishment Pacific, Victoria BC (CAN)
Abstract
Experience with the maximum entropy method of spectral analysis suggests that (a) it can produce inaccurate frequency estimates of short sample sinusoidal data: and, (b) it sometimes produces calculated values for the filter coefficients that are unduly contaminated by rounding errors. Consequently, in this report we develop an algorithm for solving the underlying least-squares problem directly, without forcing a Toeplitz structure on the model. This approach leads to more accurate frequency determination for short sample harmonic processes, and our algorithm is computationally efficient and numerically stable. The algorithm can also be applied to two other versions of the linear prediction problem. A FORTRAN program is supplied.
Report Number
DM-142-IR —
Date of publication
15 Aug 1978
Number of Pages
52
DSTKIM No
78-03075
CANDIS No
83753
Format(s):
Hardcopy;Originator's fiche received by DSIS

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