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Biomedical subjects

O V Usatenko

Publications and source records attributed to O V Usatenko.

5 recordsLinked to original sources

Rank distributions of words in correlated symbolic systems and the Zipf law.

The binary many-step Markov chain with the step-like memory function is considered as a model for the analysis of rank distributions of words in correlated stochastic symbolic systems. We prove that this distribution obeys the power law with the exponent of the order of unity in the case of rather strong persistent correlations. The Zipf law is shown to be valid for the rank distribution of words with lengths about and shorter than the correlation length in the Markov sequence. A self-similarity in the rank distribution with respect to the decimation procedure is observed.

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Competition between two kinds of correlations in literary texts.

A theory of additive Markov chains with long-range memory is used to describe the correlation properties of coarse-grained literary texts. The complex structure of the correlations in the texts is revealed. Anti-persistent correlations at small distances, L approximately < 300, and persistent ones at L approximately > 300 define this non-trivial structure. For some concrete examples of literary texts, the memory functions are obtained and their power-law behavior at long distances is disclosed. This property is shown to be a cause of self-similarity of texts with respect to the decimation procedure.

Journal Article↗

Symbolic stochastic dynamical systems viewed as binary N-step Markov chains.

A theory of systems with long-range correlations based on the consideration of binary N-step Markov chains is developed. In the model, the conditional probability that the ith symbol in the chain equals zero (or unity) is a linear function of the number of unities among the preceding N symbols. The correlation and distribution functions as well as the variance of the number of symbols in the words of arbitrary length L are obtained analytically and numerically. A self-similarity of the studied stochastic process is revealed and the similarity group transformation of the chain parameters is presented. The diffusion Fokker-Planck equation governing the distribution function of the L words is explored. If the persistent correlations are not extremely strong, the distribution function is shown to be the Gaussian with the variance being nonlinearly dependent on L. The applicability of the developed theory to the coarse-grained written and DNA texts is discussed.

Journal Article↗

Binary N-step Markov chains and long-range correlated systems.

A theory of systems with long-range correlations based on the consideration of binary N-step Markov chains is developed. In our model, the conditional probability that the ith symbol in the chain equals zero (or unity) is a linear function of the number of unities among the preceding N symbols. The correlation and distribution functions as well as the variance of number of symbols in the words of arbitrary length L are obtained analytically and numerically. If the persistent correlations are not extremely strong, the variance is shown to be nonlinearly dependent on L. A self-similarity of the studied stochastic process is revealed. The applicability of the developed theory to the coarse-grained written and DNA texts is discussed.

Bacillus subtilis↗

Bifurcation picture for gap solitons in nonlinear modulated systems.

We investigate the problem of nonlinear wave propagation in periodic media. Four different classes of periodic nonlinear media are taken into consideration: a nonlinear diatomic elastic chain, modulated nonlinear optical media, a diatomic easy-axis ferromagnetic chain, and an easy-plane antiferromagnet in an external magnetic field. The main result of our work is a qualitative analysis of all kinds of small amplitude soliton excitations with frequencies lying in the gap and near the gap of the linear wave spectrum. We also study the evolution of the system phase portrait and the bifurcation picture of the soliton solutions under changes of the medium parameters.

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