TY - JOUR

T1 - One-parameter fractional linear prediction

AU - Despotovic, Vladimir

AU - Skovranek, Tomas

AU - Peric, Zoran

N1 - Funding Information:
This work was supported in part by the Ministry of Education, Science and Technological Development of the Republic of Serbia , Grant No. TR32035 , TR33037 ; by the Slovak Research and Development Agency under the contract No.: SK-SRB-2016-0030 , SK-AT-2017-0015 , APVV-14-0892 , APVV-0482-11 ; by the Slovak Grant Agency for Science under grant VEGA 1/0908/15 ; and under the framework of the COST Action CA15225 .
Publisher Copyright:
© 2018 Elsevier Ltd

PY - 2018/7

Y1 - 2018/7

N2 - 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.

AB - 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.

KW - Fractional calculus

KW - Fractional derivative

KW - Linear prediction

KW - Optimal prediction

UR - http://www.scopus.com/inward/record.url?scp=85047895495&partnerID=8YFLogxK

U2 - 10.1016/j.compeleceng.2018.05.020

DO - 10.1016/j.compeleceng.2018.05.020

M3 - Article

AN - SCOPUS:85047895495

VL - 69

SP - 158

EP - 170

JO - Computers and Electrical Engineering

JF - Computers and Electrical Engineering

SN - 0045-7906

ER -