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Publications in Math-Net.Ru |
Citations |
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2022 |
| 1. |
V. A. Valoshka, A. I. Trubey, “On the power of tests of multidimensional discrete uniformity used for statistical analysis of random number generators”, Journal of the Belarusian State University. Mathematics and Informatics, 1 (2022), 26–37   |
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Yu. S. Kharin, V. A. Voloshko, “On the approximation of high-order binary Markov chains by parsimonious models”, Diskr. Mat., 34:3 (2022), 114–135 ; Discrete Math. Appl., 34:2 (2024), 71–87 |
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2020 |
| 3. |
Yu. S. Kharin, V. A. Valoshka, O. V. Dernakova, V. I. Malugin, A. J. Kharin, “Statistical forecasting of the dynamics of epidemiological indicators for COVID-19 incidence in the republic of belarus”, Journal of the Belarusian State University. Mathematics and Informatics, 3 (2020), 36–50 |
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V. A. Voloshko, E. V. Vecherko, “New upper bounds for noncentral chi-square cdf”, Journal of the Belarusian State University. Mathematics and Informatics, 1 (2020), 70–74 |
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2019 |
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V. A. Voloshko, Yu. S. Kharin, “Semibinomial conditionally nonlinear autoregressive models of discrete random sequences: probabilistic properties and statistical parameter estimation”, Diskr. Mat., 31:1 (2019), 72–98  ; Discrete Math. Appl., 30:6 (2020), 417–437   |
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2018 |
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Yu. S. Kharin, V. A. Voloshko, “Binomial conditionally nonlinear autoregressive model of discrete time series and its probabilistic and statistical properties”, Tr. Inst. Mat., 26:1 (2018), 95–105 |
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2016 |
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V. A. Voloshko, “Steganographic capacity for one-dimensional Markov cover} \runningtitle{Steganographic capacity for one-dimensional Markov cover} \author*[1]{Valeriy A. Voloshko} \runningauthor{V. A. Voloshko} \affil[1]{ Belarusian State University, e-mail: valeravoloshko@yandex.ru} \abstract{For shift-invariant probability measures on the set of infinite two-sided binary sequences (one-dimensional covers) we introduce the notion of capacity as a maximum portion of embedded into the cover uniformly distributed (purely random) binary sequence (message) that admits special correction of the cover restoring its distribution up to distribution of $n$-tuples (subwords of some fixed length $n$). “Special correction” is carried out using the proposed new algorithm that changes some of the cover's symbols not occupied by embedded message. The features of the introduced capacity are examined for the Markov cover. In particular, we show how capacity may be significantly increased by weakening of the standard constraint that positions for message embedding have to be chosen by independent unfair coin tosses. Experimental results are presented for correction of real steganographic covers after LSB-embedding.} \keywords{binary sequence, shift-invariant measure, steganography, capacity”, Diskr. Mat., 28:1 (2016), 19–43 ; Discrete Math. Appl., 27:4 (2017), 247–268 |
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