activity
19982024
most citedSymbolic stochastic dynamical systems viewed as binary N-step Markov chains

38 citations · 239 across the 32 of their papers we have counts for

collaborators

32 papers

cond-mat.stat-mech2024

Random telegraph processes with non-local memory

S. S. Apostolov, O. V. Usatenko, V. A. Yampol'skii +3

We study two-state (dichotomous, telegraph) random ergodic continuous-time processes with dynamics depending on their past. We take into account the history of process in an explic…

physics.data-an2023

Information temperature as a parameter of random sequence complexity

O. V. Usatenko, G. M. Pritula

In this study, we continue our exploration of the concept of information temperature as a characteristic of random sequences. We describe methods for introducing the information te…

physics.data-an2022★ 2 cited

Information entropy and temperature of the binary Markov chains

O. V. Usatenko, S. S. Melnyk, G. M. Pritula +1

We propose two different approaches for introducing the information temperature of the binary N-th order Markov chains. The first approach is based on comparing the Markov sequence…

cond-mat.stat-mech2020★ 3 cited

Memory-dependent noise-induced resonance and diffusion in non-markovian systems

S. S. Melnyk, O. V. Usatenko, V. A. Yampol'skii

We study the random processes with non-local memory and obtain new solutions of the Mori-Zwanzig equation describing non-markovian systems. We analyze the system dynamics depending…

cond-mat.stat-mech2020★ 4 cited

Correlation properties of the random linear high-order Markov chains

V. E. Vekslerchik, G. M. Pritula, S. S. Melnik +1

The aim of this paper is to study the correlation properties of random sequences with additive linear conditional probability distribution function (CPDF) and elaborate a reliable…

cond-mat.stat-mech2019★ 5 cited

Continuous stochastic processes with non-local memory

S. S. Melnyk, V. A. Yampol'skii, O. V. Usatenko

We study the non-Markovian random continuous processes described by the Mori-Zwanzig equation. As a starting point, we use the Markovian Gaussian Ornstein-Uhlenbeck process and int…