Analysis of the main provisions of the theory of parallel-hierarchical transformations

Authors

  • L. Tymchenko State University of Infrastructure and Technology
  • O. Stetsenko State University of Infrastructure and Technology
  • N. Kokryatskay State University of Infrastructure and Technology
  • V. Kaplun Vinnytsia National Technical University
  • N. Dubova Vinnytsia National Technical University

DOI:

https://doi.org/10.31649/1681-7893-2023-45-1-43-54

Keywords:

pattern recognition task, parallel-hierarchical network, parallel-hierarchical transformation

Abstract

The article presents an analysis of the main principles of parallel-hierarchical transformations theory. The continuous movement of society towards the automation of everyday life requires the creation of fundamentally new software and hardware solutions. Considering the current physical limitations of integrated circuits, it is evident that improving software processing is the way to go. The main problem lies in the increasing complexity of architecture and supporting such code. The ideas of parallel-hierarchical networks allow for a significant increase in processing speed through process parallelization while maintaining the relative simplicity of the software solution's architecture. The proposed structure of the parallel-hierarchical network allows for modelling the operation principle of a distributed neural network and forms a deterministic network using spatial-temporal division. The general rules of direct and inverse parallel-hierarchical transformation and their application to image recognition tasks are discussed. A block diagram of the algorithm for the basic model of nonlinear direct network transformation is shown. A mathematical model of direct parallel-hierarchical transformation is presented using an example. Compared to known numerical transformation methods involving simple operations like addition, the model enables complex functional signal processing in real-time scale, as well as unambiguity and reversibility with good convergence of the computational process.

Author Biographies

L. Tymchenko, State University of Infrastructure and Technology

D.Sc., professor head of Artificial intelligence systems and telecommunication technologies department

O. Stetsenko, State University of Infrastructure and Technology

postgraduate student  of Artificial intelligence systems and telecommunication technologies

N. Kokryatskay, State University of Infrastructure and Technology

Ph.D., Docent head of Artificial intelligence systems and telecommunication technologies department

N. Dubova, Vinnytsia National Technical University

senior lector of Higher Mathematics Department

References

Vernon B. Mountcastle, Modality and topographic properties of single neurons of cat's somatic sensory cortex. // Journal of Neurophysiology. 1957. No. 118, P. 268-275

J.S. Bruner. Beyond the Information Given: Studies in the Psychology of Knowing // W. W. Norton, Incorporated. 1973. 526 p.

L.I. Timchenko, N.I. Kokryatska, O.A. M.S. Hertsii Petrovskyi, D.S. Stepaniuk. Parallel-hierarchical networks for image processing. Part one - Theoretical studies // Timchenko L.I. Monograph. 2017. 467p.

V.P. Kozhemyako, L.I. Timchenko, Y.F. Kutaev, I.D. Ivasyuk Introduction to the algorithmic theory of hierarchy and parallelism of neuro-like computing environments and its application to image transformation. Basics of the theory of pyramidal network transformation of images // UMK VO. 1994. 272p.

M.M. Yatsymirskyi. Algorithmic foundations of computer tools for spectral-correlation processing of signals and images // Abstract of the thesis of the Doctor of Technical Sciences. Lviv. 1998.

T. Kohonen. Self Organization and Associative Memory: Third Edition // Springer-Verlag. New York. 1989.

L.I. Timchenko, N.I. Kokryatska, V.V. Shpakovych. Modeling of a method of parallel hierarchical transformation for fast recognition of dynamic images // EURASIP Journal on Advances in Signal Processing (25 April 2013)

L.M. Gomel. Evolutionary theory. A textbook for students of biological specialties of higher educational institutions // ASM. Poltava. 2011. 136 p.

T.I. Levchenko. European education: Convergence and Divergence: Levchenko T.I. Monograph // A new book. Vinnytsia. 2007. 656p.

S.A. Subbotin, A.A. Oleynik. Evolutionary synthesis of models of complex objects and processes // Radioelectronics and Informatics. 2007. No 2, P.99-104.

María Laura Tardivo, Paola Caymes-Scutari, Miguel Méndez-Garabetti. Hierarchical parallel model for improving performance on differential evolution Concurrency and Computation: Practice and Experience // Computer Science (25 May 2017).

J. M. White, G.D. Rohrer. Image Thresholding for Optical Character Recognition and Other Applications Requiring Character Image Extraction. // J. Res. Develop. 1983. No 27 (4), 400-411.

Houtsma, MAW, Cacace, F., & Ceri, S. Parallel hierarchical evaluation of transitive closure queries. // Proceedings of the 1st International Conference on Parallel and Distributed Information Systems. 1991. PP. 130-137. https://doi.org/10.1109/PDIS.1991.183080

Fathollah Bistouni, Mohsen Jahanshahi. Pars network: A multistage interconnection network with fault-tolerance capability // Journal of Parallel and Distributed Computing. 2015. No 75, P. 168-183.

Noriaki Sato, Masafumi Hagiwara. Parallel-hierarchical neural network for 3D object recognition. // Systems and Computers in Japan. 2004. No 35, P. 1-12. https://doi.org/10.1002/scj.10579

Ming Rao, Jian-Zhong Cha, Ji Zhou. A parallel hierarchical integrated intelligent system for engineering design automation. // Engineering Applications of Artificial Intelligence. 1991. No 4, P.145-150. https://doi.org/10.1016/0952-1976(91)90054-A

Hannah Lee, James Motes, Marco Morales, Nancy Amato. Parallel Hierarchical Composition Conflict-Based Search for Optimal Multi-Agent Pathfinding // IEEE Robotics and Automation Letters. 2021 No 6, 7001-7008. https://doi.org/10.1109/LRA.2021.3096476

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Published

2023-09-28

How to Cite

[1]
L. Tymchenko, O. Stetsenko, N. Kokryatskay, V. Kaplun, and N. Dubova, “Analysis of the main provisions of the theory of parallel-hierarchical transformations”, Опт-ел. інф-енерг. техн., vol. 45, no. 1, pp. 43–54, Sep. 2023.

Issue

Vol. 45 No. 1 (2023)

Section

OptoElectronic/Digital Methods and Systems for Image/Signal Processing

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