Specific features of the use of artificial intelligence in the development of the architecture of intelligent fault-tolerant radar systems

M. Коsovets, L. Tovstenko
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Abstract

The problem of architecture development of modern radar systems using artificial intelligence technology is considered. The main difference is the use of a neural network in the form of a set of heterogeneous neuromultimicroprocessor modules, which are rebuilt in the process of solving the problem systematically in real time by the means of the operating system. This architecture promotes the implementation of cognitive technologies that take into account the requirements for the purpose, the influence of external and internal factors. The concept of resource in general and abstract resource of reliability in particular and its role in designing a neuromultimicroprocessor with fault tolerance properties is introduced. The variation of the ratio of performance and reliability of a fault-tolerant neuromultimicroprocessor of real time with a shortage of reliability resources at the system level by means of the operating system is shown, dynamically changing the architectural appearance of the system with structural redundancy, using fault-tolerant technologies and dependable computing.
利用人工智能的具体特点开发了智能容错雷达系统的体系结构
研究了采用人工智能技术的现代雷达系统的体系结构发展问题。其主要区别在于使用了一组异构神经多微处理器模块的形式的神经网络,这些模块通过操作系统在实时系统地解决问题的过程中进行重构。这种体系结构促进了认知技术的实现,这些技术考虑到目的的需求、外部和内部因素的影响。介绍了资源的一般概念,特别是可靠性抽象资源的概念及其在设计具有容错特性的神经多微处理器中的作用。在系统级可靠性资源不足的情况下,通过操作系统实现了实时容错神经多微处理器性能与可靠性比值的变化,采用容错技术和可靠计算,动态改变了具有结构冗余的系统的体系结构外观。
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