Дата поступления: 
24.09.2018
Год: 
2018
Номер журнала (Том): 
УДК: 
004.056.55: 303.732.4: 519.1
Файл статьи: 
Страницы: 
48
63
Аннотация: 

In this paper, we consider the concept of universal combinatorial coding. Most coding methods that can be found in one whole, you can get a universal coding method. It can become a bridge that will connect the known coding methods and will serve as an impetus to the development of coding technology. Universal combinatorial lossless coding is based on combinatorics. It does not depend on the entropy of the information source and is divided into three characteristic coding branches. This division into branches helped to investigate the relationship between universal combinatorial coding and other methods. For this coding method, an efficiency estimate was made in the article. Universal combinatorial coding has theoretical significance and practical value of application

Список цитируемой литературы: 
  1. Bakulina M. P. Effektivnyj metod universal'nogo kombinatornogo kodirovaniya [Effective method of universal combinatorial coding]. Polzunovskij vestnik [Polzunovsky Herald]. , 2014, № 2. – С. 58-61.
  2. Grishin M.L. Kombinatornoe kodirovanie informacii [Combinatorial coding of information]. URL http://www. arts-union.ru/node/20
  3. Fu Z., Zhao J. Information Theory and Coding. Beijing, China: Publishing House of Electronics Industry; 2008.
  4. Huffman D. A. A method for the construction of minimum redundancy codes. Proceedings of the Institute of Radio Engineers. 1952.40(9):1098–1101.
  5. Rissanen J., Langdon G. G. Arithmetic coding. IBM Journal of Research and Development. 1979. 23(2):149–162.
  6. Kuz'min O. V., Starkov B. A. Fraktal'nye svojstva binarnyh matric, postroennyh pri pomoshchi arifmetiki treugol'nika Paskalya, i pomekhoustojchivoe kodirovanie [Fractal properties of binary matrices constructed using Pascal's triangle arithmetic, and noise-immune coding]. Sovremennye tekhnologii. Sistemnyj analiz. Modelirovanie [Modern technologies. System analysis. Modeling]. – 2016. № 4 (52). – С. 138-142.
  7. Kuz'min O.V., Starkov B. A.  Binarnye matricy, postroennye pri pomoshchi treugol'nika Paskalya, i pomekhoustojchivoe kodirovanie [Binary matrices constructed using the Pascal triangle, and noise-immune coding]. Sovremennye tekhnologii. Sistemnyj analiz. Modelirovanie [Modern technologies. System analysis. Modeling]. – 2016. № 1 (49). – С. 112-117.
  8. Zelentsov I. A. Psevdosluchajnye posledovatel'nosti i kodirovanie informacii [Pseudo-random sequences and information coding]. Voprosy estestvoznaniya [Questions of natural science], 2017, № 2 (14). – С. 30-37.
  9. Langdon G. G., Rissanen J. Compression of black-white images with arithmetic coding. IEEE Transactions on Communications Systems. 1981. 29(6):858–867.
  10. Ziv J., Lempel A.  Universal algorithm for sequential data compression. IEEE Transactions on Information Theory. 1977. 23(3):337–343.
  11. Kuz'min O. V., Starkov B. A.  Binarnye matricy s arifmetikoj treugol'nika Paskalya i simvol'nye posledovatel'nosti [Binary matrices with Pascal triangle arithmetic and character sequences]. Izvestiya Irkutskogo gosudarstvennogo universiteta. Seriya «Matematika» [News of Irkutsk State University. Series "Mathematics"]. – 2016. – Т. 18. – С. 38–47.
  12. Ziv J., Lempel A. Compression of individual sequences via variable-rate coding. IEEE Transactions on Information Theory. 1978. IT-24(5):530–536.
  13. Kuz'min O. V., Timoshenko A. A. Analiz algoritmov dekodirovaniya standarta radiosvyazi [Analyze of the algorithms of decoding of the standard-radio connection]. MIL-STD-186-141B. Vestnik Irkutskogo gosudarstvennogo tekhnicheskogo universiteta [News of Irkutsk State University. Series "Mathematics"]. – 2015, № 2 (97). – С.188–192.
  14. Kuz'min O. V. Vvedenie v perechislitel'nuyu kombinatoriku [Introduction to enumerative combinatorics].  – Irkutsk: Izd-vo Irkut.un-ta [Irkutsk University Press], 1995. – 112 с. 
  15. Kuz'min O. V., Zelentsov I. A. Kodirovanie zvukovoj informacii s pomoshch'yu algoritma perestanovok [Coding of sound information using the permutation algorithm]. Sovremennye tekhnologii. Sistemnyj analiz. Modelirovanie. [Modern technologies. System analysis. Modeling]. – 2017. № 4 (56). – С. 151-158.
  16. Jun L., Liu D-X. Research on parallel technology within section in combinatorics coding. Proceedings of the International Conference on Computer Application and System Modeling (ICCASM '10). October 2010. IEEE Press. pp. 52–56.
  17. Shu Z., Yan-li Z. CUDA of GPU High Performance Computing. Beijing, China: China Water & Power Press; 2009.
  18. Sanders J., Sanders Ed.  CUDA By Example: An Introduction to General-Purpose GPU Programming. Beijing, China: China Machine Press; 2011.
  19. Han Z., Tang K., Cui H. Parametric model for context-based adaptive binary arithmetic coding. Journal of Tsinghua University. 2009;49(4):531–534.
  20. Deng H-G., Guo S-W., Li Z-J. VQ image compression algorithm Based on Huffman Coding. Computer Engineering. 2010;36(4):218–219.
  21. Sun C., Zhou G-X. Research on the optimization of lossless compression algorithm for network transmission. Journal of Hefei University of Technology. 2012;35(6):762–766.
  22. Yang H., Liao X., Wong K-W., Zhang W., Wei P. A new block cipher based on chaotic map and group theory. Chaos, Solitons and Fractals. 2009;40(1):50–59.
  23. Wei J., Liao X., Wong K-W., Xiang T. A new chaotic cryptosystem. Chaos, Solitons and Fractals. 2006;30(5):1143–1152.
  24. Toldinas J., Stuikys V., Damasevicius R., Ziberkas G., Banionis M. Energy efficiency comparison with cipher strength of AES and Rijndael cryptographic algorithms in mobile devices. Electronics and Electrical Engineering. 2011. 108(2):11–14.