dc.contributor.author |
Cortés, J.-C.
|
es_ES |
dc.contributor.author |
Navarro-Quiles, A.
|
es_ES |
dc.contributor.author |
Romero, José-Vicente
|
es_ES |
dc.contributor.author |
Roselló, María-Dolores
|
es_ES |
dc.date.accessioned |
2020-04-17T12:51:34Z |
|
dc.date.available |
2020-04-17T12:51:34Z |
|
dc.date.issued |
2019 |
es_ES |
dc.identifier.issn |
1007-5704 |
es_ES |
dc.identifier.uri |
http://hdl.handle.net/10251/140954 |
|
dc.description.abstract |
[EN] This paper deals with the study, from a probabilistic point of view, of logistic-type differential equations with uncertainties. We assume that the initial condition is a random variable and the diffusion coefficient is a stochastic process. The main objective is to obtain the first probability density function, f_1(p,t), of the solution stochastic process, P(t,¿). To achieve this goal, first the diffusion coefficient is represented via a truncation of order N of the Karhunen¿Loève expansion, and second, the Random Variable Transformation technique is applied. In this manner, approximations, say f^N_1(p,t), of f_1(p,t) are constructed. Afterwards, we rigorously prove that f^N_1(p,t) ¿¿ f_1(p,t) as N ¿ ¿ under mild conditions assumed on input data (initial condition and diffusion coefficient). Finally, three illustrative examples are shown. |
es_ES |
dc.description.sponsorship |
This work has been partially supported by the Ministerio de Economia y Competitividad grant MTM2017-89664-P. Ana Navarro Quiles acknowledges the postdoctoral contract financed by DyCon project funding from the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programme (grant agreement No 694126-DYCON). The authors express their deepest thanks and respect to the editor and reviewers for their valuable comments. |
es_ES |
dc.language |
Inglés |
es_ES |
dc.publisher |
Elsevier |
es_ES |
dc.relation.ispartof |
Communications in Nonlinear Science and Numerical Simulation |
es_ES |
dc.rights |
Reserva de todos los derechos |
es_ES |
dc.subject |
Karhunen-Loeve expansion |
es_ES |
dc.subject |
Random Variable Transformation technique |
es_ES |
dc.subject |
First probability density function |
es_ES |
dc.subject |
Random logistic differential equation |
es_ES |
dc.subject |
Nonlinear stochastic processes |
es_ES |
dc.subject.classification |
MATEMATICA APLICADA |
es_ES |
dc.title |
Analysis of random non-autonomous logistic-type differential equations via the Karhunen-Loeve expansion and the Random Variable Transformation technique |
es_ES |
dc.type |
Artículo |
es_ES |
dc.identifier.doi |
10.1016/j.cnsns.2018.12.013 |
es_ES |
dc.relation.projectID |
info:eu-repo/grantAgreement/EC/H2020/694126/EU/Dynamic Control and Numerics of Partial Differential Equations/ |
es_ES |
dc.rights.accessRights |
Abierto |
es_ES |
dc.contributor.affiliation |
Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada |
es_ES |
dc.description.bibliographicCitation |
Cortés, J.; Navarro-Quiles, A.; Romero, J.; Roselló, M. (2019). Analysis of random non-autonomous logistic-type differential equations via the Karhunen-Loeve expansion and the Random Variable Transformation technique. Communications in Nonlinear Science and Numerical Simulation. 72:121-138. https://doi.org/10.1016/j.cnsns.2018.12.013 |
es_ES |
dc.description.accrualMethod |
S |
es_ES |
dc.relation.publisherversion |
https://doi.org/10.1016/j.cnsns.2018.12.013 |
es_ES |
dc.description.upvformatpinicio |
121 |
es_ES |
dc.description.upvformatpfin |
138 |
es_ES |
dc.type.version |
info:eu-repo/semantics/publishedVersion |
es_ES |
dc.description.volume |
72 |
es_ES |
dc.relation.pasarela |
S\374252 |
es_ES |