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A class of fast covariance least squares algorithms

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2 Author(s)
Todd, R.M. ; Sch. of Electr. Eng. & Comput. Sci., Oklahoma Univ., Norman, OK, USA ; Cruz, J.R.

A new class of fast least squares linear prediction algorithms for frequency estimation is described, and a specific example of this class of algorithms is presented in detail. A simulation for the case of single-sinusoid inputs shows that the estimates are quite sensitive to noise for frequencies near half the Nyquist frequency. A simplified error analysis seems to confirm the existence of the noise sensitivity in that range of frequencies

Published in:

Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on

Date of Conference:

3-6 Apr 1990