A.V. Volosova1, K.S. Myshenkov2, S.W. Panjukova3

1–3 Bauman Moscow State Technical University (Moscow, Russia)
1 volosova@bmstu.ru, 2 myshenkovks@bmstu.ru, 3 Panyukova@bmstu.ru

Due to the increasing complexity of computing in complex dynamic systems and the limitations of parallel, neural network, and quantum technologies currently in use, it is urgent to search for alternative approaches to computing.

The article discusses the implementation of neuromorphic computing as a way to increase the energy efficiency of a computing platform.

Neuromorphic microcircuits combined with digital architecture provide a fundamentally new solution for efficient computing. Such chips are capable of providing high-level parallelism and are characterized by ultra-low power consumption. The dynamic nature of the neuromorphic system makes it possible to combine real-time computing with management and decision-making capabilities at different levels, also in real time. The digital platform, enhanced by the functionality of the neuromorphic system, allows you to get a high-performance computing base.

Models for the implementation of a neuromorphic twin at different levels of the Intelligent Electronic Coupling system have been developed. The introduction of a neuromorphic twin into a complex dynamic system makes it possible to obtain a high-performance computing base. The neuromorphic devices used in the implementation of the doppelganger provide new possibilities for processing uncertainty due to their analog nature. On the basis of which fundamentally new models of uncertainty can be built. The neuromorphic twin has built-in properties of self-organization and heterogeneity, which opens up new possibilities for its communication with the dynamic system. The built-in management and decision-making capabilities of the neuromorphic twin provide a more convenient implementation of management and decision-making processes at different levels of the ULS system. The nature of the neuromorphic system facilitates the implementation of stable communication between neuromorphic counterparts of different types within the framework of the ULS system. Since the absence of these properties in digital counterparts leads to additional efforts to organize interaction between virtual objects within the framework of the ULS system. The neuromorphic nature of the doppelganger allows for the implementation of built-in artificial intelligence. Enhanced by built-in artificial intelligence, the neuromorphic twin can generate knowledge.

Volosova A.V., Myshenkov K.S., Panjukova S.W. Construction and use of tensor analog of quadratic dynamical systems for bifurcation prediction // Highly Available Systems. 2026. V. 22. № 2. P. 89−108. DOI: https://doi.org/10.18127/j20729472-202602-08

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