Physics – Data Analysis – Statistics and Probability
Scientific paper
2002-11-12
Physics
Data Analysis, Statistics and Probability
LaTeX2e, 16 pages, 9 figures
Scientific paper
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 i-th symbol in the chain equals zero (or unity) is a linear function of the number of unities among the preceding N symbols. The model allows exact analytical treatment. 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. A self-similarity of the studied stochastic process is revealed and the similarity transformation of the chain parameters is presented. The diffusion 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.
Usatenko O. V.
Yampol'skii V. A.
No associations
LandOfFree
Binary N-Step Markov Chain as an Exactly Solvable Model of Long-Range Correlated Systems does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Binary N-Step Markov Chain as an Exactly Solvable Model of Long-Range Correlated Systems, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Binary N-Step Markov Chain as an Exactly Solvable Model of Long-Range Correlated Systems will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-19635