Existence, Uniqueness, and Input-to-State Stability of Ground State Stationary Strong Solution of a Single-Species Model via Mountain Pass Lemma
Author(s) -
Ruofeng Rao,
Quanxin Zhu,
Jialin Huang
Publication year - 2021
Publication title -
complexity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.447
H-Index - 61
eISSN - 1099-0526
pISSN - 1076-2787
DOI - 10.1155/2021/8855351
Subject(s) - uniqueness , lemma (botany) , lyapunov function , mathematics , saddle point , exponential stability , stationary point , equilibrium point , population , stationary state , regularization (linguistics) , stability (learning theory) , ordinary differential equation , mathematical analysis , control theory (sociology) , differential equation , computer science , physics , ecology , geometry , poaceae , demography , control (management) , nonlinear system , quantum mechanics , artificial intelligence , machine learning , sociology , biology
In this study, the authors utilize mountain pass lemma, variational methods, regularization technique, and the Lyapunov function method to derive the unique existence of the positive classical stationary solution of a single-species ecosystem. Particularly, the geometric characteristic of saddle point in the mountain pass lemma guarantees that the equilibrium point is the ground state stationary solution of the ecosystem. Based on the obtained uniqueness result, the authors use the Lyapunov function method to derive the globally exponential stability criterion, which illuminates that under some suitable conditions, a certain internal competition is conducive to the global stability of the population, and a certain amount of family planning is conducive to the overall stability of the population. Most notably, the regularity technique of weak stationary solution employed in this study can also be applied to some existing literature related with time-delays reaction-diffusion systems for the purpose of regularization of weak solutions. Finally, an illuminative numerical example shows the effectiveness of the proposed methods.
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