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Two-dimensional data-block compression of information-measuring system algorithms

A. V. LevenetsPacific National University, 136, Tihookeanskaya st., Khabarovsk, 680035, RussiaD. I. Nefed’evPenza State University, 40, Krasnaya st., Penza, 440026, RussiaRuslan BazhenovSholom-Aleichem Priamursky State University, 70A, Shirokaya st., 679015, Birobidzhan, RussiaV. B. MasyaginOmsk State Technical University, 11, Mira ave., Omsk, 644050, RussiaSaida BeknazarovaTashkent University of Information Technologies named after Muhammad Al-Khwarizmi, 108, Amir Temur st., Tashkent, 100200, Uzbekistan
ABI

Abstract

Abstract The authors suggest a new approach to develop measurement data compression algorithms. According to that a data frame is considered as a bit sequence formed into a two-dimensional well-ordered linear structure. It is supposed that there is no explicit bind to the source data / specifications width within the collected structure. The researchers propose block compression algorithms. They take into account not only the relationship between one sensor readings in adjacent samples, but also the connection of the samples in one frame so that it is expected to contribute to higher compression efficiency. The studies of the proposed compression algorithms have shown that they can be effectively used for compressing data frames of information-measuring systems. The mid-compression ratio of the proposed block compression algorithms falls in the range 8.0 to 9.5, and a simple adaptive algorithm observed in the paper provides the maximum value of the average compression ratio.

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