Zobrazeno 1 - 10
of 142
pro vyhledávání: '"Shige Peng"'
Publikováno v:
Information Sciences. 621:156-171
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1e01025616874855e8ce683a6bbf1893
https://doi.org/10.1016/j.ins.2022.11.063
https://doi.org/10.1016/j.ins.2022.11.063
Publikováno v:
Digital Finance. 5:1-2
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4db687695adf0ab8ebb004629f0e80d3
https://doi.org/10.1007/s42521-023-00080-2
https://doi.org/10.1007/s42521-023-00080-2
Autor:
Shige Peng, Huilin Zhang
Publikováno v:
Journal of Theoretical Probability. 35:410-425
In this paper, we build the Wong–Zakai approximation for Stratonovich-type stochastic differential equations driven by G-Brownian motion and obtain the quasi-sure convergence rate under Holder norm by a rough path argument. As a corollary, we obtai
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::efdf5e17cc4124d122216c9b9bce9c36
https://doi.org/10.1007/s10959-020-01058-1
https://doi.org/10.1007/s10959-020-01058-1
Publikováno v:
IEEE Intelligent Systems. 35:71-84
Recently, the deep learning method has been used for solving forward–backward stochastic differential equations (FBSDEs) and parabolic partial differential equations, as it has good accuracy and performance for high-dimensional problems. In this ar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::13bcd5887ccdb4e9e03cdf48735c1054
https://doi.org/10.1109/mis.2020.2971597
https://doi.org/10.1109/mis.2020.2971597
Autor:
Xinpeng Li, Shige Peng
Publikováno v:
Stochastic Analysis, Filtering, and Stochastic Optimization ISBN: 9783030985189
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::771843a14c1409c5cd2a42fb127518e1
https://doi.org/10.1007/978-3-030-98519-6_14
https://doi.org/10.1007/978-3-030-98519-6_14
Publikováno v:
Probability, Uncertainty & Quantitative Risk; 2023, Vol. 8 Issue 1, p1-32, 32p
Autor:
Shige Peng, Xiaojun Ji
Publikováno v:
Science China Mathematics. 63:61-82
Under the framework of sublinear expectation, we introduce a new type of G-Gaussian random fields, which contains a type of spatial white noise as a special case. Based on this result, we also introduce a spatial-temporal G-white noise. Different fro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eb4baddd82ee8860febaebfffbeebf4c
https://doi.org/10.1007/s11425-018-9558-1
https://doi.org/10.1007/s11425-018-9558-1
Autor:
Shige Peng
Publikováno v:
Encyclopedia of Systems and Control ISBN: 9781447151029
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::42db8539a8e8f60470096ac03fffa858
https://doi.org/10.1007/978-3-030-44184-5_234
https://doi.org/10.1007/978-3-030-44184-5_234
In this paper, we aim to solve the high dimensional stochastic optimal control problem from the view of the stochastic maximum principle via deep learning. By introducing the extended Hamiltonian system which is essentially an FBSDE with a maximum co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::946be8d6566d22afe4d3da1b591bbe99
Publikováno v:
Probability, Uncertainty and Quantitative Risk. 7:i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::32fd9925ecae9dbe7506946b9e7ea2f7
https://doi.org/10.3934/puqr.2022010
https://doi.org/10.3934/puqr.2022010