Higher order stroboscopic averaged functions a general relationship with Melnikov functions /

In the research literature, one can find distinct notions for higher order averaged functions of regularly perturbed non-autonomous T-periodic differential equations of the kind x 0 = εF(t, x,ε). By one hand, the classical (stroboscopic) averaging method provides asymptotic estimates for its solutio...

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Elmentve itt :
Bibliográfiai részletek
Szerző: Novaes Douglas D.
Dokumentumtípus: Folyóirat
Megjelent: 2021
Sorozat:Electronic journal of qualitative theory of differential equations
Kulcsszavak:Differenciálegyenlet
doi:10.14232/ejqtde.2021.1.77

Online Access:http://acta.bibl.u-szeged.hu/73729
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520 3 |a In the research literature, one can find distinct notions for higher order averaged functions of regularly perturbed non-autonomous T-periodic differential equations of the kind x 0 = εF(t, x,ε). By one hand, the classical (stroboscopic) averaging method provides asymptotic estimates for its solutions in terms of some uniquely defined functions gi ’s, called averaged functions, which are obtained through nearidentity stroboscopic transformations and by solving homological equations. On the other hand, a Melnikov procedure is employed to obtain bifurcation functions fi ’s which controls in some sense the existence of isolated T-periodic solutions of the differential equation above. In the research literature, the bifurcation functions fi ’s are sometimes likewise called averaged functions, nevertheless, they also receive the name of Poincaré–Pontryagin–Melnikov functions or just Melnikov functions. While it is known that f1 = Tg1, a general relationship between gi and fi is not known so far for i ≥ 2. Here, such a general relationship between these two distinct notions of averaged functions is provided, which allows the computation of the stroboscopic averaged functions of any order avoiding the necessity of dealing with near-identity transformations and homological equations. In addition, an Appendix is provided with implemented Mathematica algorithms for computing both higher order averaging functions. 
695 |a Differenciálegyenlet 
856 4 0 |u http://acta.bibl.u-szeged.hu/73729/1/ejqtde_2021_077.pdf  |z Dokumentum-elérés