Features of computational processes based on SM – transformation

Authors

  • T.B. Martyniuk Vinnytsia National Technical University
  • D.O. Katashynskyi Vinnytsia National Technical University
  • M.V. Mykytyuk Vinnytsia National Technical University
  • M.O. Zaitsev Vinnytsia National Technical University

DOI:

https://doi.org/10.31649/1681-7893-2022-44-2-32-37

Keywords:

difference slice, vector number array, sorting, ranking

Abstract

The features and functionality of processing of the one – dimensional (vector) arrays of numerical data by the use of computational method with the formation of difference slices are considered. At the base of this method SM – transformation principles are used. The allocation of the minimum of non-zero component of the element array in this case is considered as the formation of the internal processing threshold and is the basic procedure of SM - transformation in each processing cycle. As a result, not only the operation of parallel multi-operand summation of the number array is realized, but also there is an opportunity to restore the initial number array, as well as to sort its elements according to the growth of their numerical values and to form their ranks. Two matrices of binary masks are used for this, that are formed during the processing, which are the matrices of zero and positive criterion, respectively, inherent in the elements of the current difference  slices. In addition, in each processing cycle the internal thresholds form a vector of internal thresholds as a result, which takes part in restoring the elements of the initial array. The it is presented in the article the basic relations of difference slice processing, and the examples that confirm their validity using data presented in the form of a table.

Author Biographies

T.B. Martyniuk, Vinnytsia National Technical University

doctor of technology of Sciences, professor of the Department of Computer Engineering

D.O. Katashynskyi, Vinnytsia National Technical University

graduate student of the Department of Computer Engineering

M.V. Mykytyuk, Vinnytsia National Technical University

graduate student of the Department of Computer Engineering

M.O. Zaitsev, Vinnytsia National Technical University

graduate student of the Department of Computer Engineering

References

T. B. Martyniuk, Recursive algorithms for multi-operand information processing. Monograph. Vinnytsia: "Universum" Vinnytsia, 2000. - 216 p.

T. B. Martyniuk, V. V. Khomiuk, Peculiarities of the mathematical model of discrete SM transformation, Mathematical machines and systems, No. 4, p. 145-155, 2010.

T. B. Martynyuk, L. I. Timchenko, A. V. Kozhemyako, L. M. Kupershtein, Effectiveness of cut-by-cut processing of vector arrays of data, Mathematical machines and systems, No. 2, p. 60-67. 2017.

I. E. A. Yatsenko, Regular schemes of address sorting and search algorithms, Control systems and machines, No. 5, p. 61-66, 2004.

I. G. Tsmots, V. Ya. Antoniv, V. O. Parubchak, Parallel-vertical sorting of one-dimensional data by the method of merging using counting, Collection of scientific papers. Institute of Modeling Problems in Energy, Vol. 68, p. 92-100, 2013.

I. G. Tsmots, V. Ya. Antoniv, Algorithms and parallel structures of data sorting by the method of insertion, Scientific Bulletin of NLTU, Vol. 261, p. 340-350, 2016.

R. Sedgewick R, Fundamental algorithms in C++. Analysis / Data structures / Sorting / Search. St. Petersburg: DiaSoftYUP LLC, 2002. - 688 p.

U. Pratt, Digital image processing. Book 2. M.: Mir, 1982. – 480 p.

E. F. Ochyn, Computational systems of image processing. L.: Energoatomizdat, 1989. – 136p.

K. I. Kucherenko, E. F. Ochyn, Processors of two-dimensional median filtering of images based on sorting networks, Avtometriya, No. 2, p. 13-19, 1988.

I. G. Tsmots, Information technologies and specialized tools for processing signals and images in real time. Lviv: UAD Publishing House, 2005. – 228p.

T. Kohonen, Associative memory devices. M.: Mir, 1982. – 384 p.

D. E. Knuth, The Art of Programming. T. 3 Sorting and searching. M.: Izdatelsky dom "Williams", 2003. - 832 p.

T. B. Martyniuk, B. I. Krukivskyi, A model of a parallel sorter for an associative processor, Bulletin of the Vinnytsia Polytechnic Institute, No. 5, p. 49-55, 2020. doi: https://doi.org/10.31649/1997-9266-2020-152-5-49-55

T. B. Martyniuk, B. I. Krukivskyi, Peculiarities of the parallel sorting algorithm with the formation of ranks, Cybernetics and system analysis, No. 1(58), p. 31-36, 2022. doi: https://doi.org/10.31649/1997-9266-2020-152-5-49-55

T. B. Martyniuk, A. V. Kozhem'yako, B. I. Krukivskyi, A. G. Buda, Associative operations based on difference-slice data processing, Bulletin of the Khmelnytskyi National University. Technical sciences, No. 4, p. 159-163, 2022. doi: https://doi.org/10.31891/2307–5732–2022-311-4-159-163.

W. Wójcik, S. Pavlov, M Kalimoldayev. (2019). Information Technology in Medical Diagnostics II. London: Taylor & Francis Group, CRC Press, Balkema book. – 336 Pages, https://doi.org/10.1201/9780429057618.

Highly linear Microelectronic Sensors Signal Converters Based on Push-Pull Amplifier Circuits / edited by Waldemar Wojcik and Sergii Pavlov, Monograph, (2022) NR 181, Lublin, Comitet Inzynierii Srodowiska PAN, 283 Pages. ISBN 978-83-63714-80-2.

Downloads

Abstract views: 90

Published

2023-01-20

How to Cite

[1]
T. Martyniuk, D. Katashynskyi, M. Mykytyuk, and M. Zaitsev, “Features of computational processes based on SM – transformation”, Опт-ел. інф-енерг. техн., vol. 44, no. 2, pp. 32–37, Jan. 2023.

Issue

Section

OptoElectronic/Digital Methods and Systems for Image/Signal Processing

Metrics

Downloads

Download data is not yet available.