Abstract
In this paper, we present a cancer system in a continuous state as well as some numerical results. We present discretization methods, e.g., the Euler method, the Taylor series expansion method, and the Runge–Kutta method, and apply them to the cancer system. We studied the stability of the fixed points in the discrete cancer system using the new version of Marotto’s theorem at a fixed point; we prove that the discrete cancer system is chaotic. Finally, we present numerical simulations, e.g., Lyapunov exponents and bifurcations diagrams.
Funder
King Abdulaziz University
Subject
General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)
Reference17 articles.
1. The dynamics of an optimally controlled tumor model: A case study
2. A Validated Mathematical Model of Cell-Mediated Immune Response to Tumor Growth
3. Bifurcations and Chaotic Dynamics in a Tumour-Immune-Virus System
4. Dynamics in a Discrete-Time Three Dimensional Cancer System;Kamel;Int. J. Appl. Math.,2019
5. Selection of optimal numerical method for implementation of Lorenz Chaotic system on FPGA;Karakaya;Int. Res. Eng. J.,2018
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