Zobrazeno 1 - 10
of 60
pro vyhledávání: '"Hongjiong Tian"'
Publikováno v:
Entropy, Vol 24, Iss 6, p 808 (2022)
The correlation-based network is a powerful tool to reveal the influential mechanisms and relations in stock markets. However, current methods for developing network models are dominantly based on the pairwise relationship of positive correlations. T
Externí odkaz:
https://doaj.org/article/d282f12b94984dbc9b12ce38cdbfc723
Publikováno v:
Applied Mathematics Letters. 139:108540
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::135afca9785134ab90efe6ff5ee79408
https://doi.org/10.1016/j.aml.2022.108540
https://doi.org/10.1016/j.aml.2022.108540
Publikováno v:
Applied Numerical Mathematics. 161:218-232
We develop and analyze an hp-version of the discontinuous Galerkin time-stepping method for linear Volterra integral equations with weakly singular kernels. We derive a priori error bound in the L 2 -norm that is fully explicit in the local time step
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2f79bb37ee1c324460990f2dd5af8029
https://doi.org/10.1016/j.apnum.2020.11.006
https://doi.org/10.1016/j.apnum.2020.11.006
Autor:
Quanwei Ren, Hongjiong Tian
Publikováno v:
Computational and Applied Mathematics. 41
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::87f4871d26bc6cb39d9a9576d529d9e3
https://doi.org/10.1007/s40314-022-01824-3
https://doi.org/10.1007/s40314-022-01824-3
Autor:
Quanwei Ren, Hongjiong Tian
Publikováno v:
Applied Numerical Mathematics. 150:27-37
In this paper, we are concerned with numerical methods for solving stochastic differential equations with Poisson-driven jumps. We construct a class of compensated θ-Milstein methods and study their mean-square convergence and asymptotic mean-square
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d83a5f9d47dc6dfd2cb8d0934008ffc5
https://doi.org/10.1016/j.apnum.2019.09.009
https://doi.org/10.1016/j.apnum.2019.09.009
Publikováno v:
Discrete & Continuous Dynamical Systems - S. 13:2603-2617
We propose a new family of functionally-fitted block \begin{document}$ \theta $\end{document} -methods for numerically solving ordinary differential equations which integrates a chosen set of linearly independent functions exactly. The advantage of s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b166a8a0f86dbe42005dacf807befd72
https://doi.org/10.3934/dcdss.2020164
https://doi.org/10.3934/dcdss.2020164
Publikováno v:
Computational and Applied Mathematics. 40
In this paper, we consider highly oscillatory second-order differential equations $$\ddot{x}(t)+\Omega ^2x(t)=g(x(t))$$ with a single frequency confined to the linear part, and $$\Omega $$ is singular. It is known that the asymptotic-numerical solver
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3e9e14b2207e8512d97451db804b6abc
https://doi.org/10.1007/s40314-021-01675-4
https://doi.org/10.1007/s40314-021-01675-4
Autor:
Zhenglu, Jiang, Hongjiong, Tian
Publikováno v:
In Acta Mathematica Scientia 2010 30(1):281-288
Publikováno v:
Advances in Computational Mathematics. 47
We present an alternative approach proposed by Albrecht to derive general order conditions for Runge-Kutta-Nystrom methods and relate it to the classical RKN-theory. The RKN-methods are treated as composite linear methods to yield the general order c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e842193bc24c98d83e1f28fd1029003f
https://doi.org/10.1007/s10444-021-09894-3
https://doi.org/10.1007/s10444-021-09894-3
Autor:
Hongjiong Tian, Quanwei Ren
Publikováno v:
International Journal of Computer Mathematics. 97:1363-1379
The main aim of this study is to propose a class of generalized two-step Milstein methods for solving Ito stochastic differential equations. We study their mean-square consistency and mean-square c...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f90209e662c95cb39a2cba1181ad13e6
https://doi.org/10.1080/00207160.2019.1618846
https://doi.org/10.1080/00207160.2019.1618846