Article (Scientific journals)
One-parameter fractional linear prediction
Despotovic, Vladimir; Skovranek, Tomas; Peric, Zoran
2018In Computers and Electrical Engineering, 69, p. 158.170
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Keywords :
Linear prediction; Optimal prediction; Fractional calculus; Fractional derivative
Abstract :
[en] The one-parameter fractional linear prediction (FLP) is presented and the closed-form expressions for the evaluation of FLP coefficients are derived. Contrary to the classical first-order linear prediction (LP) that uses one previous sample and one predictor coefficient, the one-parameter FLP model is derived using the memory of two, three or four samples, while not increasing the number of predictor coefficients. The first-order LP is only a special case of the proposed one-parameter FLP when the order of fractional derivative tends to zero. Based on the numerical experiments using test signals (sine test waves), and real-data signals (speech and electrocardiogram), the hypothesis for estimating the fractional derivative order used in the model is given. The one-parameter FLP outperforms the classical first-order LP in terms of the prediction gain, having comparable performance with the second-order LP, although using one predictor coefficient less.
Disciplines :
Computer science
Author, co-author :
Despotovic, Vladimir ;  University of Belgrade > Technical Faculty in Bor
Skovranek, Tomas;  Technical University of Kosice > BERG Faculty
Peric, Zoran;  University of Nis > Faculty of Electronic Engineering
External co-authors :
yes
Language :
English
Title :
One-parameter fractional linear prediction
Publication date :
July 2018
Journal title :
Computers and Electrical Engineering
ISSN :
1879-0755
Publisher :
Elsevier, New York, United Kingdom
Volume :
69
Pages :
158.170
Peer reviewed :
Peer Reviewed verified by ORBi
Funders :
Ministry of Education, Science and Technological Development of the Republic of Serbia
Slovak Research and Development Agency
Slovak Grant Agency for Science
COST action
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since 24 October 2019

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