The Experts below are selected from a list of 324 Experts worldwide ranked by ideXlab platform
Soledad Torres - One of the best experts on this subject based on the ideXlab platform.
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Numerical Scheme for Stochastic Differential Equations Driven by Fractional Brownian Motion with $$ 1/4
Journal of Theoretical Probability, 2020Co-Authors: Héctor Araya, Jorge A. León, Soledad TorresAbstract:In this article, we study a numerical scheme for stochastic differential equations driven by fractional Brownian motion with Hurst parameter $$ H \in \left( 1/4, 1/2 \right) $$ H ∈ 1 / 4 , 1 / 2 . Toward this end, we apply Doss–Sussmann representation of the solution and an approximation of this representation using a first-Order Taylor Expansion. The obtained rate of convergence is $$n^{-2H +\rho }$$ n - 2 H + ρ , for $$\rho $$ ρ small enough.
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Numerical Scheme for Stochastic Differential Equations Driven by Fractional Brownian Motion with $$ 1/4
Journal of Theoretical Probability, 2019Co-Authors: Héctor Araya, Jorge A. León, Soledad TorresAbstract:In this article, we study a numerical scheme for stochastic differential equations driven by fractional Brownian motion with Hurst parameter $$ H \in \left( 1/4, 1/2 \right) $$ H ∈ 1 / 4 , 1 / 2 . Toward this end, we apply Doss–Sussmann representation of the solution and an approximation of this representation using a first-Order Taylor Expansion. The obtained rate of convergence is $$n^{-2H +\rho }$$ n - 2 H + ρ , for $$\rho $$ ρ small enough.
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Numerical scheme for stochastic differential equations driven by fractional Brownian motion with 1/4 < H < 1/2
arXiv: Probability, 2019Co-Authors: Héctor Araya, Jorge A. León, Soledad TorresAbstract:In this article, we study a numerical scheme for stochastic differential equations driven by fractional Brownian motion with Hurst parameter H in (1/4; 1/2). Towards this end, we apply Doss-Sussmann representation of the solution and an approximation of this representation using a first Order Taylor Expansion. The obtained rate of convergence is n^(2H+rho), for rho small enough.
Binbin Zhao - One of the best experts on this subject based on the ideXlab platform.
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second Order Taylor Expansion boundary element method for the second Order wave diffraction problem
Engineering Analysis With Boundary Elements, 2015Co-Authors: Wenyang Duan, Jikang Chen, Binbin ZhaoAbstract:Abstract A new Boundary Element Method (BEM) is developed for the solution of the induced velocity at the sharp corners in the context of potential flow. This method is based on the framework of low-Order direct BEM to solve the Boundary Integral Equation (BIE), which mainly applies the Taylor Expansion to the dipole strength in the BIE, reserves the first-Order, second-Order and mixed derivatives, and finally solves the corresponding tangential derivatives with respect to the field point in the BIE to form the closed equations. So the method is named the second-Order Taylor Expansion Boundary Element Method (the 2nd Order TEBEM), which can accurately solve the induced velocity on the non-smooth boundary, compared with the low-Order BEM (Constant panel method), and all of the singular integrals in 2nd Order TEBEM can be solved analytically. Its implementation is quite easy compared with high-Order BEM. The characteristics of 2nd Order TEBEM are studied by various wave diffraction problems, and the results of 2nd Order TEBEM are compared with the analytical solutions and other numerical results, which show satisfactory agreements.
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second Order Taylor Expansion boundary element method for the second Order wave radiation problem
Applied Ocean Research, 2015Co-Authors: W Y Duan, J K Chen, Binbin ZhaoAbstract:Abstract A novel Boundary Element Method (BEM) named the second-Order Taylor Expansion Boundary Element Method (the 2nd Order TEBEM) is developed for the solution of the second-Order wave radiation velocity potential and sum-frequency wave loads for floating bodies. The radiation condition is enforced by a hybrid method of the multi-transmitting formula and damping zone. For the interior domain problem of a cube and a sphere, numerical results demonstrate that the 2nd Order TEBEM can accurately solve the first and second-Order gradients of velocity potential on the no-smoothed and smoothed boundary compared to the low-Order BEM. The double frequency forces acting on the truncated cylinder are calculated under finite water depth. The agreement between the 2nd Order TEBEM and others' numerical results is good. Moreover, all of the singular integrals in the 2nd Order TEBEM can be solved analytically, so its implementation is much easier compared to the high-Order BEM.
Katsushi Ikeuchi - One of the best experts on this subject based on the ideXlab platform.
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calculating possible local displacement of curve objects using improved screw theory
International Conference on Robotics and Automation, 2003Co-Authors: Jun Takamatsu, Koichi Ogawara, Hiroshi Kimura, Katsushi IkeuchiAbstract:Various methods to recognize assembly tasks using possible local displacement of objects have been proposed. To calculate this displacement, the screw theory is employed. It is equivalent to the first Order Taylor Expansion of the displacement. However, such methods can treat polyhedral objects only. Because the screw theory cannot treat curvature information of objects. In this paper, we propose a method to calculate possible local displacement of curve objects using improved screw theory, which is equivalent to the second Order Taylor Expansion of the displacement, and verify the validity of the proposed method.
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ICRA - Calculating possible local displacement of curve objects using improved screw theory
2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422), 1Co-Authors: Jun Takamatsu, Koichi Ogawara, Hiroshi Kimura, Katsushi IkeuchiAbstract:Various methods to recognize assembly tasks using possible local displacement of objects have been proposed. To calculate this displacement, the screw theory is employed. It is equivalent to the first Order Taylor Expansion of the displacement. However, such methods can treat polyhedral objects only. Because the screw theory cannot treat curvature information of objects. In this paper, we propose a method to calculate possible local displacement of curve objects using improved screw theory, which is equivalent to the second Order Taylor Expansion of the displacement, and verify the validity of the proposed method.
Héctor Araya - One of the best experts on this subject based on the ideXlab platform.
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Numerical Scheme for Stochastic Differential Equations Driven by Fractional Brownian Motion with $$ 1/4
Journal of Theoretical Probability, 2020Co-Authors: Héctor Araya, Jorge A. León, Soledad TorresAbstract:In this article, we study a numerical scheme for stochastic differential equations driven by fractional Brownian motion with Hurst parameter $$ H \in \left( 1/4, 1/2 \right) $$ H ∈ 1 / 4 , 1 / 2 . Toward this end, we apply Doss–Sussmann representation of the solution and an approximation of this representation using a first-Order Taylor Expansion. The obtained rate of convergence is $$n^{-2H +\rho }$$ n - 2 H + ρ , for $$\rho $$ ρ small enough.
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Numerical Scheme for Stochastic Differential Equations Driven by Fractional Brownian Motion with $$ 1/4
Journal of Theoretical Probability, 2019Co-Authors: Héctor Araya, Jorge A. León, Soledad TorresAbstract:In this article, we study a numerical scheme for stochastic differential equations driven by fractional Brownian motion with Hurst parameter $$ H \in \left( 1/4, 1/2 \right) $$ H ∈ 1 / 4 , 1 / 2 . Toward this end, we apply Doss–Sussmann representation of the solution and an approximation of this representation using a first-Order Taylor Expansion. The obtained rate of convergence is $$n^{-2H +\rho }$$ n - 2 H + ρ , for $$\rho $$ ρ small enough.
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Numerical scheme for stochastic differential equations driven by fractional Brownian motion with 1/4 < H < 1/2
arXiv: Probability, 2019Co-Authors: Héctor Araya, Jorge A. León, Soledad TorresAbstract:In this article, we study a numerical scheme for stochastic differential equations driven by fractional Brownian motion with Hurst parameter H in (1/4; 1/2). Towards this end, we apply Doss-Sussmann representation of the solution and an approximation of this representation using a first Order Taylor Expansion. The obtained rate of convergence is n^(2H+rho), for rho small enough.
Hsiuying Wang - One of the best experts on this subject based on the ideXlab platform.
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Variance estimation for nucleotide substitution models.
Molecular Phylogenetics and Evolution, 2015Co-Authors: Weishan Chen, Hsiuying WangAbstract:The current variance estimators for most evolutionary models were derived when a nucleotide substitution number estimator was approximated with a simple first Order Taylor Expansion. In this study, we derive three variance estimators for the F81, F84, HKY85 and TN93 nucleotide substitution models, respectively. They are obtained using the second Order Taylor Expansion of the substitution number estimator, the first Order Taylor Expansion of a squared deviation and the second Order Taylor Expansion of a squared deviation, respectively. These variance estimators are compared with the existing variance estimator in terms of a simulation study. It shows that the variance estimator, which is derived using the second Order Taylor Expansion of a squared deviation, is more accurate than the other three estimators. In addition, we also compare these estimators with an estimator derived by the bootstrap method. The simulation shows that the performance of this bootstrap estimator is similar to the estimator derived by the second Order Taylor Expansion of a squared deviation. Since the latter one has an explicit form, it is more efficient than the bootstrap estimator.
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Improved variance estimators for one- and two-parameter models of nucleotide substitution.
Journal of theoretical biology, 2008Co-Authors: Hsiuying Wang, Yun Huei TzengAbstract:The current variance estimators for Jukes and Cantor's one-parameter model and Kimura's two-parameter model tend to underestimate the true variances when the true proportion of differences between the two sequences under study is not small. In this paper, we developed improved variance estimators, using a higher-Order Taylor Expansion and empirical methods. The new estimators outperform the conventional estimators and provide accurate estimates of the true variances.