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Probl. Peredachi Inf., 2016, Volume 52, Issue 1, Pages 101–109 (Mi ppi2198)  

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.

Funding Agency Grant Number
Russian Foundation for Basic Research 15-07-01851
Supported in part by the Russian Foundation for Basic Research, project no. 15-07-01851.


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English version:
Problems of Information Transmission, 2016, 52:1, 92–99

Bibliographic databases:

UDC: 621.391.15
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

Citation in format AMSBIB
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\pages 101--109
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\pages 92--99
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  • Проблемы передачи информации Problems of Information Transmission
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