The present paper is devoted to the problems of practical stability with respect to h-manifolds for impulsive control differential equations with variable impulsive perturbations. We will consider these problems in light of the Lyapunov–Razumikhin method of piecewise continuous functions. The new results are applied to an impulsive control cellular neural network model with variable impulsive perturbations.
<abstract><p>In this paper, motivated by the advantages of the generalized conformable derivatives, an impulsive conformable Cohen–Grossberg-type neural network model is introduced. The impulses, which can be also considered as a control strategy, are at fixed instants of time. We define the notion of practical stability with respect to manifolds. A Lyapunov-based analysis is conducted, and new criteria are proposed. The case of bidirectional associative memory (BAM) network model is also investigated. Examples are given to demonstrate the effectiveness of the established results.</p></abstract>
This article is devoted to the creation of a mathematical model processing the output signal of video surveillance systems, based on information about the characteristics of the signals of the objects of observation, in order to protect cultural heritage.
The subject of the study is the relationship between the structure and parameters of the output signal, certain changes in the situation in the area of observation and detection of a signal from foreign objects against the background of noise.
Typical physical conditions for the functioning of video surveillance systems are defined and general recommendations for maintaining the operating point are offered. Algorithms have been developed that realize the functionality of the optimal detector device by numerical methods.
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