Analysis of fractional stochastic systems driven by fractional Brownian motion with general memory kernel
[EN] Fractional stochastic differential equations (FSDEs) driven by fractional Brownian motion (fBm) have attracted growing attention due to their ability to model systems exhibiting non-Markovian dynamics and long-range dependence, which naturally arise in many real-world phenomena characterized by...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2026 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:dnet:riunet______::035de99ea4ab0fdb21f8637a0ea54d1d |
| Acceso en línea: | https://riunet.upv.es/handle/10251/233489 |
| Access Level: | acceso abierto |
| Palabra clave: | Ffractional Brownian motion Mild solutions Picard iteration approach Fixed point approach |
| Sumario: | [EN] Fractional stochastic differential equations (FSDEs) driven by fractional Brownian motion (fBm) have attracted growing attention due to their ability to model systems exhibiting non-Markovian dynamics and long-range dependence, which naturally arise in many real-world phenomena characterized by hereditary and persistent randomness. In this work, we establish the existence and uniqueness of mild solutions using the Picard iteration technique for the case where the Hurst parameter (1 ) satisfies H is an element of 2, 1 . Moreover, we establish the approximate controllability of the systems under suitable conditions. To generalize the theoretical framework, we employ the Caputo-Katugampola fractional derivative (CKFD), thereby extending the analysis to a broader class of fractional stochastic systems. |
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