Asymptotic and Analytic Methods in Stochastic Evolutionary Symptoms

This book illustrates a number of asymptotic and analytic approaches applied for the study of random evolutionary systems, and considers typical problems for specific examples. In this case, constructive mathematical models of natural processes are used, which more realistically describe the trajectories of diffusion-type processes, rather than those of the Wiener process.

We examine models where particles have some free distance between two consecutive collisions. At the same time, we investigate two cases: the Markov evolutionary system, where the time during which the particle moves towards some direction is distributed exponentially with intensity parameter λ; and the semi-Markov evolutionary system, with arbitrary distribution of the switching process. Thus, the models investigated here describe the motion of particles with a finite speed and the proposed random evolutionary process with characteristics of a natural physical process: free run and finite propagation speed. In the proposed models, the number of possible directions of evolution can be finite or infinite.

Dmitri Koroliouk is a Doctor of Sciences, Professor at the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, and leading researcher at the Institute of Mathematics, and at the Institute of Telecommunications and Global Information Space of the National Academy of Sciences of Ukraine. He is also Head of the Digital Innovation Laboratory at UNESCO Interdisciplinary Chair in Biotechnology and Bioethics, at the University of Rome Tor Vergata, Italy.

Igor Samoilenko is a Doctor of Sciences, Professor at the Taras Shevchenko National University of Kyiv, and Professor at the Institute for Applied System Analysis, part of the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”.