Zhovnovatiy Kirill Evgenievich (Graduate student
The Kosygin Russian State University
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This study aims to develop an analytical model describing the dynamics of processing stochastic information inputs in cognitive systems, accounting for significant variations in the processing speed for different information types. Input events are formalized using random process theory as a marked Poisson point process, where each event is defined by three key parameters: a random occurrence time, a random volume of transmitted information, and a random coefficient determining the system-specific speed of its processing. The state of the cognitive system at any given time is modeled as the accumulated sum of decaying response functions for each incoming event. These functions depend on the time elapsed since the information arrival, its initial volume, and the assigned processing speed coefficient.
The core result of the work is the rigorous derivation of analytical expressions for the mathematical expectations of two critical quantities: the total volume of information successfully processed by the system by a given time, and the volume of information remaining unprocessed (current "load"). A fundamental applicability constraint of the model is established: it is most adequate and informative when the characteristic time for the system to process a unit of information is comparable to the average time interval between consecutive event arrivals.
The obtained results provide a foundation for solving practical problems, such as optimizing the sequence of control actions on cognitive systems (biological or artificial), predicting and managing their workload, and for clearly specifying technical requirements for designed intelligent and cognitive systems, including requirements for throughput capacity and resilience to information flows.
Keywords:cognitive system, random point process, response function, processing speed coefficient.
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Citation link:
Zhovnovatiy K. E. DYNAMICS OF PROCESSING OF STOCHASTIC INFORMATION INFLUENCES IN COGNITIVE SYSTEMS // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2025. -№07. -С. 85-90 DOI 10.37882/2223-2966.2025.07.12 |
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