7 results on '"Li, Jingzhi"'
Search Results
2. Adaptive neural network surrogate model for solving the implied volatility of time-dependent American option via Bayesian inference.
- Author
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Qian, Yiyuan, Zhang, Kai, Li, Jingzhi, and Wang, Xiaoshen
- Subjects
ARTIFICIAL neural networks ,BAYESIAN analysis ,INVERSE problems ,FINITE element method ,SAMPLING methods - Abstract
In this paper, we propose an adaptive neural network surrogate method to solve the implied volatility of American put options, respectively. For the forward problem, we give the linear complementarity problem of the American put option, which can be transformed into several standard American put option problems by variable substitution and discretization in the temporal direction. Thus, the price of the option can be solved by primal-dual active-set method using numerical transformation and finite element discretization in spatial direction. For the inverse problem, we give the framework of the general Bayesian inverse problem, and adopt the direct Metropolis-Hastings sampling method and adaptive neural network surrogate method, respectively. We perform some simulations of volatility in the forward model with one- and four-dimension to compare the point estimates and posterior density distributions of two sampling methods. The superiority of adaptive surrogate method in solving the implied volatility of time-dependent American options are verified. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
3. Determining a Random Schrödinger Operator: Both Potential and Source are Random.
- Author
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Li, Jingzhi, Liu, Hongyu, and Ma, Shiqi
- Subjects
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RANDOM operators , *SCHRODINGER operator , *INVERSE problems , *OPERATOR theory , *BACKSCATTERING , *INVERSE scattering transform , *PSEUDODIFFERENTIAL operators - Abstract
We study an inverse scattering problem associated with a Schrödinger system where both the potential and source terms are random and unknown. The well-posedness of the forward scattering problem is first established in a proper sense. We then derive two unique recovery results in determining the rough strengths of the random source and the random potential, by using the corresponding far-field data. The first recovery result shows that a single realization of the passive scattering measurements uniquely recovers the rough strength of the random source. The second one shows that, by a single realization of the backscattering data, the rough strength of the random potential can be recovered. The ergodicity is used to establish the single realization recovery. The asymptotic arguments in our study are based on techniques from the theory of pseudodifferential operators and microlocal analysis. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
4. Convexification for an inverse parabolic problem.
- Author
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Klibanov, Michael V, Li, Jingzhi, and Zhang, Wenlong
- Subjects
- *
INVERSE problems , *NUMERICAL functions , *GLOBAL analysis (Mathematics) - Abstract
A convexification-based numerical method for a coefficient inverse problem for a parabolic PDE is presented. The key element of this method is the presence of the so-called Carleman weight function in the numerical scheme. Convergence analysis ensures the global convergence of this method, as opposed to the local convergence of the conventional least squares minimization techniques. Numerical results demonstrate a good performance. [ABSTRACT FROM AUTHOR]
- Published
- 2020
- Full Text
- View/download PDF
5. Two gesture-computing approaches by using electromagnetic waves.
- Author
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Wang, Xianchao, Guo, Yukun, Li, Jingzhi, and Liu, Hongyu
- Subjects
ELECTROMAGNETIC waves ,MAXWELL equations ,ELECTROMAGNETIC measurements ,HUMAN body ,INVERSE problems ,COMPUTER equipment - Abstract
We are concerned with a novel sensor-based gesture input/ instruction technology which enables human beings to interact with computers conveniently. The human being wears an emitter on the finger or holds a digital pen that generates a time harmonic point charge. The inputs/instructions are performed through moving the finger or the digital pen. The computer recognizes the instruction by determining the motion trajectory of the dynamic point charge from the collected electromagnetic field measurement data. The identification process is mathematically modelled as a dynamic inverse source problem for time-dependent Maxwell's equations. From a practical point of view, the point source should be assumed to move in an unknown inhomogeneous background medium, which models the human body and the surroundings. Moreover, a salient feature is that the electromagnetic radiated data are only collected in a limited aperture. For the inverse problem, we develop, from the respectively deterministic and stochastic viewpoints, a dynamic direct sampling method and a modified particle filter method. Both approaches can effectively recover the motion trajectory. Rigorous theoretical justifications are presented for the mathematical modelling and the proposed recovery methods. Extensive numerical experiments are conducted to illustrate the promising features of the two proposed recognition approaches. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
6. Enhanced approximate cloaking by SH and FSH lining.
- Author
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Li, Jingzhi, Liu, Hongyu, and Sun, Hongpeng
- Subjects
- *
APPROXIMATION theory , *MATHEMATICAL regularization , *INVERSE problems , *HELMHOLTZ equation , *GROUP schemes (Mathematics) , *NUMERICAL analysis - Abstract
We consider approximate cloaking from a regularization viewpoint introduced in Kohn et al (2008 Inverse Problems 24 015016) for EIT and further investigated in Kohn et al (2010 Commun. Pure Appl. Math. 63 0973-1016) and Liu (2009 Inverse Problems 25 045006) for the Helmholtz equation. The cloaking schemes given by Kohn et al and Liu are shown to be (optimally) within | ln ρ|-1 in 2D and ρ in 3D of perfect cloaking, where ρ denotes the regularization parameter. In this paper, we show that by employing a soundhard layer right outside the cloaked region, one could (optimally) achieve ρN in RN, N ≥ 2, which significantly enhances the near-cloak. We then develop a cloaking scheme by making use of a lossy layer with well-chosen parameters. The lossy-layer cloaking scheme is shown to possess the same cloaking performance as the one with a sound-hard layer. Moreover, it is shown that the lossy layer could be taken as a finite realization of the sound-hard layer. Numerical experiments are also presented to assess the cloaking performances of all the cloaking schemes for comparisons. [ABSTRACT FROM AUTHOR]
- Published
- 2012
- Full Text
- View/download PDF
7. Imaging multiple magnetized anomalies by geomagnetic monitoring.
- Author
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Chen, Rongliang, Deng, Youjun, Gao, Yang, Li, Jingzhi, and Liu, Hongyu
- Subjects
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MAGNETIC anomalies , *GEOMAGNETISM , *EARTH'S core , *GEOMAGNETIC variations , *INVERSE problems , *NUMERICAL analysis - Abstract
The presence of magnetized anomalies in the shell of the Earth interrupts its geomagnetic field. We consider the inverse problem of identifying the anomalies by monitoring the variation of the geomagnetic field. Motivated by the theoretical unique identifiability result in [7] , we develop a novel numerical scheme of locating multiple magnetized anomalies. In our study, we do not assume the source that generates the geomagnetic field, and the medium configurations of the Earth's core and the magnetized anomalies are a-priori known. The core of the reconstruction scheme is a novel imaging functional whose quantitative behaviours can be used to identify the anomalies. Both rigorous analysis and extensive numerical experiments are provided to verify the effectiveness and promising features of the proposed reconstruction scheme. • Magnetic anomalies detection from geomagnetic monitoring is practically important and challenging. • Based on a sophisticated geomagnetic model, a novel reconstruction scheme is proposed and developed. • In our method, the geomagnetic source and the medium configuration of the Earth's core are both not a-priori known. • The core is a novel imaging functional whose promising features are both theoretically and computationally verified. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
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