ALGORITHMS FOR LEAST-SQUARES LINEAR PREDICTION AND MAXIMUM ENTROPY SPECTRAL ANALYSIS. PART I: THEORY

Authors
  1. Barrodale, I.
  2. Erickson, R.E.
Corporate Authors
Defence Research Establishment Pacific, Victoria BC (CAN)
Abstract
Experience with the maximum entropy spectral analysis (MESA) method suggests that (1) it can produce inaccurate frequency estimates of short sample sinusoidal data, and (2) it sometimes produces calculated values for the filter coefficients that are unduly contaminated by rounding errors. Consequently, in this report an algorithm, is developed for solving the underlying least-squares linear prediction (LSLP) 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.
Report Number
REPR-80-1 —
Date of publication
01 Jan 1980
Number of Pages
13
Reprinted from
Geophysics, vol 45, no 3, 1980, p 420-432
DSTKIM No
80-02187
CANDIS No
89873
Format(s):
Hardcopy;Originator's fiche received by DSIS

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