Reference : Audio signal processing using fractional linear prediction
Scientific journals : Article
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/40761
Audio signal processing using fractional linear prediction
English
Skovranek, Tomas mailto [Technical University of Kosice (TUKE) > BERG Faculty]
Despotovic, Vladimir mailto [University of Belgrade > Technical Faculty in Bor]
Jun-2019
Mathematics
MDPI AG
7
7
Yes
International
2227-7390
Switzerland
[en] audio signal processing ; linear prediction ; fractional derivative ; musical signal
[en] Fractional linear prediction (FLP), as a generalization of conventional linear prediction (LP), was recently successfully applied in different fields of research and engineering, such as biomedical signal processing, speech modeling and image processing. The FLP model has a similar design as the conventional LP model, i.e., it uses a linear combination of “fractional terms” with different orders of fractional derivative. Assuming only one “fractional term” and using limited number of previous samples for prediction, FLP model with “restricted memory” is presented in this paper and the closed-form expressions for calculation of FLP coefficients are derived. This FLP model is fully comparable with the widely used low-order LP, as it uses the same number of previous samples, but less predictor coefficients, making it more efficient. Two different datasets, MIDI Aligned Piano Sounds (MAPS) and Orchset, were used for the experiments. Triads representing the chords composed of three randomly chosen notes and usual Western musical chords (both of them from MAPS dataset) served as the test signals, while the piano recordings from MAPS dataset and orchestra recordings from the Orchset dataset served as the musical signal. The results show enhancement of FLP over LP in terms of model complexity, whereas the performance is comparable.
http://hdl.handle.net/10993/40761
10.3390/math7070580
https://www.mdpi.com/2227-7390/7/7/580

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