scholarly journals Oscillations of Numerical Solutions for Nonlinear Delay Differential Equations in the Control of Erythropoiesis

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Qi Wang ◽  
Jiechang Wen

We consider the oscillations of numerical solutions for the nonlinear delay differential equations in the control of erythropoiesis. The exponentialθ-method is constructed and some conditions under which the numerical solutions oscillate are presented. Moreover, it is proven that every nonoscillatory numerical solution tends to the equilibrium point of the continuous system. Numerical examples are given to illustrate the main results.

2012 ◽  
Vol 2012 ◽  
pp. 1-17
Author(s):  
Qi Wang ◽  
Jiechang Wen

This paper deals with the oscillations of numerical solutions for the nonlinear delay differential equations in physiological control systems. The exponentialθ-method is applied top′(t)=β0ωμp(t−τ)/(ωμ+pμ(t−τ))−γp(t)and it is shown that the exponentialθ-method has the same order of convergence as that of the classicalθ-method. Several conditions under which the numerical solutions oscillate are derived. Moreover, it is proven that every nonoscillatory numerical solution tends to positive equilibrium of the continuous system. Finally, the main results are illustrated with numerical examples.


2017 ◽  
Vol 2017 ◽  
pp. 1-8
Author(s):  
X. Liu ◽  
Y. M. Zeng

A stability theory of nonlinear impulsive delay differential equations (IDDEs) is established. Existing algorithm may not converge when the impulses are variable. A convergent numerical scheme is established for nonlinear delay differential equations with variable impulses. Some stability conditions of analytical and numerical solutions to IDDEs are given by the properties of delay differential equations without impulsive perturbations.


2021 ◽  
Vol 23 (11) ◽  
pp. 99-109
Author(s):  
T. Muthukumar ◽  
◽  
T. Jayakumar ◽  
D.Prasantha Bharathi ◽  
◽  
...  

In this paper, we develop the numerical solutions of certain type called Fuzzy Delay Differential Equations(FDE) by using fifth order Runge-Kutta method for fuzzy differential equations. This method based on the seikkala derivative and finally we discuss the numerical examples to illustrate the theory.


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