Invariant Continuation of Discrete Multi-Valued Functions and Their Implementation

Kabulov, Anvar; Normatov, I. H.; Urunbaev, Erkin; Muhammadiev, Firdavs

doi:10.1109/iemtronics52119.2021.9422486

Cited by 17 publications

(2 citation statements)

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“…An algorithm operator was developed, which is considered correct for problem Z, represents the sum of q operators from the model for calculating estimates, and is described by a set of 3 • n • m • q (where n is the number of predetermined features, m is the number of reference objects, q is the set of recognized objects) numerical parameters. An operator belonging to the linear closure of a model of the type of calculation of estimates was constructed [19][20][21][22]. The completeness of the linear closure of this model was proven for all problems in which for each class there is at least one stationary pair (u, v), and this correct algorithm is written explicitly.…”

Section: Introductionmentioning

confidence: 99%

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Algebraic Recognition Approach in IoT Ecosystem

Kabulov,

Saymanov,

Babadjanov

et al. 2024

Mathematics

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The solution to the problem of identifying objects in the IoT ecosystem of the Aral region is analyzed. The problem of constructing a correct algorithm with linear closure operators of a model for calculating estimates for identifying objects in the IoT ecosystem of the Aral region is considered. An algorithm operator is developed, which is considered correct for the problem Z, is the sum of q operators of the assessment calculation model, and is described by a set of numerical parameters 3·n·m·q, where n is the number of specified features, m is the number of reference objects, and q is the set of recognized objects. Within the framework of the algebraic approach, several variants of linear combinations of recognition operators are constructed, the use of which gives the correct answer on the control material, and this is proven in the form of theorems. The constructed correct recognition algorithms, which are the easiest to use, where there is no optimization procedure, make it possible to quickly solve the issue of identifying incoming information flows in the IoT ecosystem of the Aral region.

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Section: Introductionmentioning

confidence: 99%

“…From inequality [19], it is easy to see that for each object from Q the proximity function for this S over the reference set S i , Ω = {(u, v)} is equal to 1. Therefore, b ij = N, i = r i , .…”

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confidence: 99%