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

O. V. Usatenko, V. A. Yampol’skii, K. E. Kechedzhy, and S. S. Mel’nyk
Phys. Rev. E 68, 061107 – Published 24 December 2003
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Abstract

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.

  • Received 17 July 2003

DOI:https://doi.org/10.1103/PhysRevE.68.061107

©2003 American Physical Society

Authors & Affiliations

O. V. Usatenko* and V. A. Yampol’skii

  • A. Ya. Usikov Institute for Radiophysics and Electronics, Ukrainian Academy of Science, 12 Proskura Street, 61085 Kharkov, Ukraine

K. E. Kechedzhy and S. S. Mel’nyk

  • Department of Physics, Kharkov National University, 4 Svoboda Square, Kharkov 61077, Ukraine

  • *Email address: usatenko@ire.kharkov.ua

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Issue

Vol. 68, Iss. 6 — December 2003

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