This submission contains functions implementing the fractional linear prediction (FLP) models to estimate the one-dimensional signal. Two versions of FLP are implemented.
The first approach to FLP is using the whole history of the signal ("full" memory) - function flp_f.m. The second approach to FLP uses the "restricted" memory (restricted to two, three or four previous samples) - function flp_r.m.
The methods, models and applications implemented in the form of the proposed functions were presented in the works , . The MATLAB implementation of the discretization of the fractional order derivative can be found in .
 Tomas Skovranek, Vladimir Despotovic: Signal prediction using fractional derivative models. In: Handbook of Fractional Calculus with Applications, Volume 8: Applications in Engineering, Life and Social Sciences, Part B, Pages 179-205. De Gruyter, 2019.
 Vladimir Despotovic, Tomas Skovranek, Zoran Peric: One-parameter fractional linear prediction, Computers & Electrical Engineering, vol. 69, July 2018, Pages 158-170 (Included in Special Issue on Signal Processing, March 2018).
 Igor Podlubny, Tomas Skovranek, Blas M. Vinagre Jara: Matrix approach to discretization of ODEs and PDEs of arbitrary real order, MathWorks, Inc., Matlab Central File Exchage, 2008 (Updated 04 Mar 2016).