This article is cited in 6 scientific papers (total in 6 papers)
Engineering Mathematics
Simplification of statistical description of quantum entanglement of multidimensional biometric data using symmetrization of paired correlation matrices
Abstract:
The aim of the paper is to simplify the description of quantum entanglement of multidimensional biometric data and data of another nature. We use a correlation symmetrization procedure based on conservation of quantum superposition entropy codes, supported on the outputs of neural networks converter of biometric data. We give a nomogram of parameter connection having the same correlation with the output entropy for codes with the length 2, 4, 8,…, 256 bits and the formula to convert the coordinate system, simplifying connection of entropy and quantum entanglement value of multidimensional data. We claim that synthesis of correct analytical models having high dimensions connecting quantum entanglement and quantum superposition is possible only for symmetrical mathematical constructions. Obtaining asymmetrical correct data is possible only by processing real biometric images of another nature.
Keywords:
quantum superposition, quantum entanglement, neural network converter of biometric code, symmetrization of multidimensional correlative matrix, entropy.
Citation:
A. I. Ivanov, A. V. Bezyayev, A. I. Gazin, “Simplification of statistical description of quantum entanglement of multidimensional biometric data using symmetrization of paired correlation matrices”, J. Comp. Eng. Math., 4:2 (2017), 3–13
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\by A.~I.~Ivanov, A.~V.~Bezyayev, A.~I.~Gazin
\paper Simplification of statistical description of quantum entanglement of multidimensional biometric data using symmetrization of paired correlation matrices
\jour J. Comp. Eng. Math.
\yr 2017
\vol 4
\issue 2
\pages 3--13
\mathnet{http://mi.mathnet.ru/jcem86}
\crossref{https://doi.org/10.14529/jcem170201}
\mathscinet{http://mathscinet.ams.org/mathscinet-getitem?mr=3670936}
\elib{https://elibrary.ru/item.asp?id=29454741}
Linking options:
https://www.mathnet.ru/eng/jcem86
https://www.mathnet.ru/eng/jcem/v4/i2/p3
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A Gazin, A Ivanov, A Malygin, A Isaeva, “Statistical data representation in the context of increasing construction efficiency”, J. Phys.: Conf. Ser., 1614:1 (2020), 012040
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