On two-dimensional polynomial predictors

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A4 Artikkeli konferenssijulkaisussa
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2020
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Research Services
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Language
en
Pages
5
2254-2258
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28th European Signal Processing Conference, EUSIPCO 2020 - Proceedings, European Signal Processing Conference
Abstract
Many signals in nature and engineering systems can be locally modeled as relatively low degree polynomials, thus one-dimensional polynomial predictive filters are useful especially in time-critical systems. The goal of this paper is to introduce the two-dimensional polynomial predictive FIR filters and present few of their properties. First we discuss previous main results in one-dimensional polynomial predictive filters. Then we show how to find the coefficients and the system functions of the minimum area polynomial predictor, and we present the recursive form for the system function of a minimum area polynomial predictor. Finally, we approach the general form of 2D polynomial predictors.
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DOI
10.23919/Eusipco47968.2020.9287438
Citation
Astola, J, Neuvo, Y & Rusu, C 2020, On two-dimensional polynomial predictors . in 28th European Signal Processing Conference, EUSIPCO 2020 - Proceedings ., 9287438, European Signal Processing Conference, IEEE, pp. 2254-2258, European Signal Processing Conference, Amsterdam, Netherlands, 24/08/2020 . https://doi.org/10.23919/Eusipco47968.2020.9287438
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https://urn.fi/URN:NBN:fi:aalto-202101271669
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