The use of linear prediction in data compression is reviewed. For purposes of John Makhoul; Published in Proceedings of the IEEE. This paper gives an. Linear Prediction: A Tutorial Review. Authors: Makhoul, J. Publication: Proc. IEEE , Volume 63, p. Publication Date: 00/ Origin: GONG. Keywords. J. Makhoul, “Linear prediction A tutorial review,” Proc. IEEE, Vol. 63, pp. , Apr.

Author: Kirg Zulkigal
Country: Brunei Darussalam
Language: English (Spanish)
Genre: Personal Growth
Published (Last): 7 November 2009
Pages: 254
PDF File Size: 2.12 Mb
ePub File Size: 3.25 Mb
ISBN: 800-2-52949-697-3
Downloads: 85151
Price: Free* [*Free Regsitration Required]
Uploader: Shakakus

Skip to search form Skip to main content.

Linear prediction: A tutorial review – Semantic Scholar

The signal is modeled as a linear combination of its past values and present and past values of a hypothetical input to a system whose output is the given signal. In the frequency domain, this is equivalent to modeling the signal spectrum by a pole-zero spectrum.


The major part of aa paper is devoted to all-pole models. The model parameters are obtained by a least squares analysis in the time domain.

This paper has highly influenced other papers.

Linear prediction: A tutorial review

This paper has 3, citations. From This Paper Figures, tables, and topics from this paper.

Least squares Search for additional papers on this topic. Topics Discussed in This Paper. Least squares Data compression Stationary process Arabic numeral 0.

Linear Prediction: A Tutorial Review

Quantization signal processing Spectral density Coefficient Noise shaping. Citations Publications citing this paper. Showing of 1, extracted citations.

Artificial bandwidth extension of narrowband speech-enhanced speech quality and intelligibility in mobile devices Laura Laaksonen Citation Statistics 3, Citations 0 ’76 ’86 ’97 ’08 ‘ Semantic Scholar estimates that this publication has 3, citations based on the available data. See our FAQ for additional information.

References Publications referenced by this paper. Showing of 40 references.

A spectral characterization of the ill-conditioning in numerical deconvolution Michael P. On periodicity in series of related terms. Optimal least squares time – domain synthesis of recursive digital filters. Pole – zero modeling using cepstral prediction. Recursion filters for digital processing. Analysis of the difference limear log mean and mean log averaging.


By clicking accept or continuing to use the site, you tutrial to the terms outlined in our Privacy PolicyTerms of Serviceand Dataset License.