Stability, bifurcation and transition to chaos in a model of immunosensor based on lattice differential equations with delay
In the work we proposed the model of immunosensor, which is based on the system of lattice differential equations with delay. The conditions of local asymptotic stability for endemic state are gotten. For this purpose we have used method of Lyapunov functionals. It combines general approach to const...
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| Dokumentumtípus: | Folyóirat |
| Megjelent: |
2018
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| Sorozat: | Electronic journal of qualitative theory of differential equations
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| Kulcsszavak: | Differenciálegyenlet - késleltetett, Bifurkáció, Bioszenzorok |
| Online Access: | http://acta.bibl.u-szeged.hu/55697 |
| LEADER | 01856nas a2200217 i 4500 | ||
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| 005 | 20260224081030.0 | ||
| 008 | 181106s2018 hu o 000 eng d | ||
| 022 | |a 1417-3875 | ||
| 040 | |a SZTE Egyetemi Kiadványok Repozitórium |b hun | ||
| 041 | |a eng | ||
| 100 | 1 | |a Martsenyuk Vasyl | |
| 245 | 1 | 0 | |a Stability, bifurcation and transition to chaos in a model of immunosensor based on lattice differential equations with delay |h [elektronikus dokumentum] / |c Martsenyuk Vasyl |
| 260 | |c 2018 | ||
| 300 | |a 1-31 | ||
| 490 | 0 | |a Electronic journal of qualitative theory of differential equations | |
| 520 | 3 | |a In the work we proposed the model of immunosensor, which is based on the system of lattice differential equations with delay. The conditions of local asymptotic stability for endemic state are gotten. For this purpose we have used method of Lyapunov functionals. It combines general approach to construction of Lyapunov functionals of the predator–prey models with lattice differential equations. Numerical examples have showed the influence on stability of model parameters. From our numerical simulations, we have found evidence that chaos can occur through variation in the time delay. Namely, as the time delay was increased, the stable endemic solution changed at a critical value of τ to a stable limit cycle. Further, when increasing the time delay, the behavior changed from convergence to simple limit cycle to convergence to complicated limit cycles with an increasing number of local maxima and minima per cycle until at sufficiently high time delay the behavior became chaotic. | |
| 695 | |a Differenciálegyenlet - késleltetett, Bifurkáció, Bioszenzorok | ||
| 700 | 0 | 2 | |a Kłos-Witkowska Aleksandra |e aut |
| 700 | 0 | 2 | |a Sverstiuk Andriy |e aut |
| 856 | 4 | 0 | |u http://acta.bibl.u-szeged.hu/55697/1/ejqtde_2018_027.pdf |z Dokumentum-elérés |