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Journal Neurocomputers №4 for 2024 г.
Article in number:
Сyberphysical representation of robots of the neuro-network collective of automata on a chip
Type of article: scientific article
DOI: https://doi.org/10.18127/j19998554-202404-06
UDC: 004.32
Authors:

V.N. Ruchkin1, V.A. Fulin2, B.V. Kostrov3, D.V. Grigorenko4, E.V. Ruchkina5

1 Academy of the Federal Penitentiary Service of Russia (Ryazan, Russia)

2 Ryazan State University named after S. A. Yesenin (Ryazan, Russia)

3 Ryazan State Radio Engineering University (Ryazan, Russia)

4 JSC NPO Ryazanpribor (Ryazan, Russia)

5 Ryazan State Agrotechnological University named after P.A. Kostychev (Ryazan, Russia)

1 v.ruchkin@365.rsu.edu.ru, 2 v.fulin@365.rsu.edu.ru, 3 kostrov.b.v@evm.rsreu.ru, 4 gdvcesium@rambler.ru, 5 ek-ruchkina@yandex.ru

Abstract:

The article examines modern innovative technologies, which are a continuation, generalization of previously created technologies, deepening and expanding existing concepts, their application in new areas and directions of development of society. The possibilities of a significant leap forward of the above technologies are shown due to the effective use and successful transition within the framework of continuity and compatibility of hardware and software security for citizens and tourists to 5G and 6G technologies, unmanned transport management and virtual reality addition, etc. Based on analysis, abstract synthesis, minimization and structural synthesis, a conceptual model of joint design of hardware and software of the Mealy and Moore automata is proposed due to the classification of control options for a team of algorithms and a team of neural network automata and robots based on a tensor computer on a K1879VM 8YA chip and a tensor module NM Card.

Based on the importance of modern mobile CPS and the areas of application of various sectors of industry, economics and social services, the requirements, challenges and feasible implementations of architectures for the joint design of a neural network collective of automata in the form of a robot on a chip using abstract Mealy and Moore automata and a collective of automata are formed. The interchangeability and equivalence of Mealy and Moore automata ensure the invariance of options and the ability to check the performance of one relative to the other. By creating one closest model, you receive confirmation of functionality through another. This versatility of using both models proves the unambiguity and adequacy of the decisions made.

Analysis, abstract synthesis, minimization and structural synthesis are used to formalize a conceptual model of hardware-software co-design (Co-Design) of robots based on Mealy and Moore automata.

The cyber physical representation of the theoretical - multiple approach and analysis of the equivalence of information processing routines from the point of view of the concept of joint design of hardware and software allows for a unified and holistic study of clustering processes, parallel organization at the level of microarchitecture and microarchitecture in order to increase operational efficiency, versatility, and scalability and optimization of energy consumption.

The simulation results are presented as a description of the control of an expert system for the joint selection of hardware and software of a robot based on MYAMPSK or MCMPSoS through the nuclear organization of the CPS microarchitecture. Depending on the initial set of algorithms based on the tensor computer on the K1879VM 8Ya chip or the NM Card tensor module, it is proposed to implement the above areas of end-to-end technologies as tools for processing structured and unstructured data.

Pages: 56-68
For citation

Ruchkin V.N., Fulin V.A., Kostrov B.V., Grigorenko D.V., Ruchkina E.V. Сyberphysical representation of robots of the neuro-network collective of automata on a chip. Neurocomputers. 2024. V. 26. № 4. Р. 56-68. DOI: https://doi.org/10.18127/j19998554-202404-06 (In Russian)

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Date of receipt: 19.05.2024
Approved after review: 25.06.2024
Accepted for publication: 26.07.2024