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Problemy Peredachi Informatsii, 2016, Volume 52, Issue 1, Pages 101–109
(Mi ppi2198)
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This article is cited in 8 scientific papers (total in 8 papers)
Source Coding
Time series prediction based on data compression methods
A. S. Lysyaka, B. Ya. Ryabkoba a Novosibirsk State University, Novosibirsk, Russia
b Institute of Computational Technologies, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
Abstract:
We propose efficient (“fast” and low memory consuming) algorithms for universal-coding-based prediction methods for real-valued time series. Previously, for such methods it was only proved that the prediction error is asymptotically minimal, and implementation complexity issues have not been considered at all. The provided experimental results demonstrate high precision of the proposed methods.
Received: 19.03.2015 Revised: 19.12.2015
Citation:
A. S. Lysyak, B. Ya. Ryabko, “Time series prediction based on data compression methods”, Probl. Peredachi Inf., 52:1 (2016), 101–109; Problems Inform. Transmission, 52:1 (2016), 92–99
Linking options:
https://www.mathnet.ru/eng/ppi2198 https://www.mathnet.ru/eng/ppi/v52/i1/p101
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Abstract page: | 425 | Full-text PDF : | 81 | References: | 63 | First page: | 31 |
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