Results 201 to 210 of about 28,903,831 (255)
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A mollification method for a Cauchy problem for the Helmholtz equation
International Journal of Computer Mathematics, 2017ABSTRACTThe Cauchy problem for the Helmholtz equation is considered. This problem is severely ill-posed, that is, the solution does not depend continuously on the data.
Z. P. Li, C. Xu, M. Lan, Z. Qian
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Computers & Mathematics with Applications, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhang, Wen +3 more
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhang, Wen +3 more
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International Journal of Computer Mathematics, 2023
We consider solving the Cauchy problem of the Schrödinger equation with potential-free field by a mollification regularization method in this work. By convolving the measured data with the Dirichlet kernel, the ill-posed case is turned into a well-posed ...
Lan Yang, Lin Zhu, Shangqin He
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We consider solving the Cauchy problem of the Schrödinger equation with potential-free field by a mollification regularization method in this work. By convolving the measured data with the Dirichlet kernel, the ill-posed case is turned into a well-posed ...
Lan Yang, Lin Zhu, Shangqin He
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A mollification regularization method for identifying the time-dependent heat source problem
Journal of Engineering Mathematics, 2016zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yang, Fan, Fu, Chu-Li, Li, Xiao-Xiao
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Mathematical Methods in the Applied Sciences
ABSTRACTThis study investigates the solution of an ill‐posed time‐fractional order Schrödinger equation using a mollification regularization technique of the Dirichlet kernel. The Dirichlet regularized solution is obtained through convolution of the Dirichlet kernel with real measured data.
Lan Yang +3 more
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ABSTRACTThis study investigates the solution of an ill‐posed time‐fractional order Schrödinger equation using a mollification regularization technique of the Dirichlet kernel. The Dirichlet regularized solution is obtained through convolution of the Dirichlet kernel with real measured data.
Lan Yang +3 more
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Numerical analytic continuation by a mollification method based on Hermite function expansion
Inverse Problems, 2012The numerical analytic continuation of a function f(z) = f(x + iy) on a strip is discussed in this paper. Data are only given approximately on the real axis. A mollification method based on expanded Hermite functions has been introduced to deal with the ill-posedness of the problem.
Zhen-yu Zhao
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Some Applications of the Mollification Method
2001The Mollification Method is a filtering procedure that is appropriate for the regularization of a variety of ill-posed problems. In this review, we briefly introduce the method, including its main feature, which is its ability to automatically select regularization parameters.
C. E. Mejía, D. A. Murio, S. Zhan
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An a posteriori mollification method for the heat equation backward in time
Journal of Inverse and Ill-posed Problems, 2016Abstract The heat equation backward in time u t
N. Duc
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Applied Spectroscopy, 2018
Baseline drift is a commonly identified and severe problem in Raman spectra, especially for biological samples. The main cause of baseline drift in Raman spectroscopy is fluorescence generated within the sample. If left untreated, it will affect the following qualitative or quantitative analysis. In this paper, an adaptive and fully automated baseline
Hao Chen +2 more
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Baseline drift is a commonly identified and severe problem in Raman spectra, especially for biological samples. The main cause of baseline drift in Raman spectroscopy is fluorescence generated within the sample. If left untreated, it will affect the following qualitative or quantitative analysis. In this paper, an adaptive and fully automated baseline
Hao Chen +2 more
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A New Mollification Method for Numerical Differentiation of 2D Periodic Functions
2009 International Joint Conference on Computational Sciences and Optimization, 2009In this paper, we present a new method for numerical differentiation of bivariate periodic functions when a set of noisy data is given. TSVD is chosen as the needed regularization technique. It turns out the new method coincides with some type of truncated Fourier series approach. A numerical example is also given to show the efficiency of the method.
Zhenyu Zhao +3 more
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