One-parameter fractional linear prediction. (July 2018)

• Record Type: Journal Article
• Authors: Despotovic, Vladimir; Skovranek, Tomas; Peric, Zoran
• Is Part Of: Computers & electrical engineering. Volume 69(2018)
• Page Start: 158
• Page End: 170
• Publication Date: 2018-07
• Subjects: Linear prediction -- Optimal prediction -- Fractional calculus -- Fractional derivative; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2018.05.020
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: 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.