In this paper, a space-time spectral method for solving an inverse problem in the Korteweg–de Vries equation is considered. Optimal order of convergence of the semi-discrete method is obtained in L2{L^{2}}-norm. The discrete schemes of the method are based on the modified Fourier pseudospectral method in spatial direction and the Legendre-tau method in temporal direction. The nonlinear term is computed via the fast Fourier transform and fast Legendre transform. The method is implemented by the explicit-implicit iterative method. Numerical results are given to show the accuracy and capability of this space-time spectral method.
{"title":"Determination of an unknown coefficient in the Korteweg–de Vries equation","authors":"Lin Sang, Yan Qiao, Hua Wu","doi":"10.1515/jiip-2024-0008","DOIUrl":"https://doi.org/10.1515/jiip-2024-0008","url":null,"abstract":"In this paper, a space-time spectral method for solving an inverse problem in the Korteweg–de Vries equation is considered. Optimal order of convergence of the semi-discrete method is obtained in <jats:inline-formula> <jats:alternatives> <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:msup> <m:mi>L</m:mi> <m:mn>2</m:mn> </m:msup> </m:math> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_jiip-2024-0008_eq_0190.png\"/> <jats:tex-math>{L^{2}}</jats:tex-math> </jats:alternatives> </jats:inline-formula>-norm. The discrete schemes of the method are based on the modified Fourier pseudospectral method in spatial direction and the Legendre-tau method in temporal direction. The nonlinear term is computed via the fast Fourier transform and fast Legendre transform. The method is implemented by the explicit-implicit iterative method. Numerical results are given to show the accuracy and capability of this space-time spectral method.","PeriodicalId":50171,"journal":{"name":"Journal of Inverse and Ill-Posed Problems","volume":"34 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141529250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Inverse spectral problems are considered for the discontinuous Dirac operator with complex-value weight and the spectral parameter boundary conditions. We investigate some properties of spectral characteristics and show that the potential can be uniquely determined by the Weyl-type function or by two spectra on the whole interval.
{"title":"Inverse problems for the eigenparameter Dirac operator with complex weight","authors":"Ran Zhang, Kai Wang, Chuan-Fu Yang","doi":"10.1515/jiip-2024-0032","DOIUrl":"https://doi.org/10.1515/jiip-2024-0032","url":null,"abstract":"Inverse spectral problems are considered for the discontinuous Dirac operator with complex-value weight and the spectral parameter boundary conditions. We investigate some properties of spectral characteristics and show that the potential can be uniquely determined by the Weyl-type function or by two spectra on the whole interval.","PeriodicalId":50171,"journal":{"name":"Journal of Inverse and Ill-Posed Problems","volume":"66 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141523347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we consider the simplified Levenberg–Marquardt method for nonlinear ill-posed inverse problems in Hilbert spaces for obtaining stable approximations of solutions to the ill-posed nonlinear equations of the form <jats:inline-formula> <jats:alternatives> <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mrow> <m:mrow> <m:mi>F</m:mi> <m:mo></m:mo> <m:mrow> <m:mo stretchy="false">(</m:mo> <m:mi>u</m:mi> <m:mo stretchy="false">)</m:mo> </m:mrow> </m:mrow> <m:mo>=</m:mo> <m:mi>y</m:mi> </m:mrow> </m:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_jiip-2023-0090_eq_0323.png"/> <jats:tex-math>{F(u)=y}</jats:tex-math> </jats:alternatives> </jats:inline-formula>, where <jats:inline-formula> <jats:alternatives> <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mrow> <m:mi>F</m:mi> <m:mo>:</m:mo> <m:mrow> <m:mrow> <m:mi mathvariant="script">𝒟</m:mi> <m:mo></m:mo> <m:mrow> <m:mo stretchy="false">(</m:mo> <m:mi>F</m:mi> <m:mo stretchy="false">)</m:mo> </m:mrow> </m:mrow> <m:mo>⊂</m:mo> <m:mi>𝖴</m:mi> <m:mo>→</m:mo> <m:mi>𝖸</m:mi> </m:mrow> </m:mrow> </m:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_jiip-2023-0090_eq_0325.png"/> <jats:tex-math>{F:mathcal{D}(F)subsetmathsf{U}tomathsf{Y}}</jats:tex-math> </jats:alternatives> </jats:inline-formula> is a nonlinear operator between Hilbert spaces <jats:inline-formula> <jats:alternatives> <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mi>𝖴</m:mi> </m:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_jiip-2023-0090_eq_0402.png"/> <jats:tex-math>{mathsf{U}}</jats:tex-math> </jats:alternatives> </jats:inline-formula> and <jats:inline-formula> <jats:alternatives> <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mi>𝖸</m:mi> </m:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_jiip-2023-0090_eq_0403.png"/> <jats:tex-math>{mathsf{Y}}</jats:tex-math> </jats:alternatives> </jats:inline-formula>. The method is defined as follows: <jats:disp-formula> <jats:alternatives> <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mrow> <m:mrow> <m:msubsup> <m:mi>u</m:mi> <m:mrow> <m:mi>n</m:mi> <m:mo>+</m:mo> <m:mn>1</m:mn> </m:mrow> <m:mi>δ</m:mi> </m:msubsup> <m:mo>=</m:mo> <m:mrow> <m:msubsup> <m:mi>u</m:mi> <m:mi>n</m:mi> <m:mi>δ</m:mi> </m:msubsup> <m:mo>-</m:mo> <m:mrow> <m:msup> <m:mrow> <m:mo stretchy="false">(</m:mo> <m:mrow> <m:mrow> <m:msubsup> <m:mi>T</m:mi> <m:mn>0</m:mn> <m:mo>∗</m:mo> </m:msubsup> <m:mo></m:mo> <m:msub> <m:mi>T</m:mi> <m:mn>0</m:mn> </m:msub> </m:mrow> <m:mo>+</m:mo> <m:mrow> <m:msub> <m:mi>α</m:mi> <m:mi>n</m:mi> </m:msub> <m:mo></m:mo> <m:mi>I</m:mi> </m:mrow> </m:mrow> <m:mo stretchy="false">)</m:mo> </m:mrow> <m:mrow> <m:mo>-</m:mo> <m:mn>1</m:mn> </m:mrow> </m:msup> <m:mo></m:mo> <m:msubsup> <m:mi>T</m:mi> <m:mn>0</m:mn> <m:mo>∗</m:mo> </m:msubsup> <m:mo></m:mo> <m:m
在本文中,我们考虑了希尔伯特空间中非线性失当逆问题的简化 Levenberg-Marquardt 方法,以获得形式为 F ( u ) = y {F(u)=y} 的失当非线性方程的稳定近似解,其中 F : 𝒟 ( F ) ⊂ 𝖴 → 𝖸 {F:mathcardt =y} 。 其中 F : 𝒟 ( F ) ⊂ 𝖴 → 𝖸 {F:mathcal{D}(F)subsetmathsf{U}tomathsf{Y}} 是希尔伯特空间 𝖴 {mathsf{U}} 和 𝖸 {mathsf{Y}} 之间的非线性算子。 .该方法定义如下: u n + 1 δ = u n δ - ( T 0 ∗ T 0 + α n I ) - 1 T 0 ∗ ( F ( u n δ ) - y δ ) 。 , u_{n+1}^{delta}=u_{n}^{delta}-(T_{0}^{ast}T_{0}+alpha_{n}I)^{-1}T_{0}^{% ast}(F(u_{n}^{delta})-y^{delta}), 其中 T 0 = F ′ ( u 0 ) {T_{0}=F^{prime}(u_{0})} and T 0 ∗ = F ′ ( u 0 )∗ {T_{0}^{ast}=F^{prime}(u_{0})^{ast}} . .这里 F ′ ( u 0 ) {F^{prime}(u_{0})} 表示 F 在初始猜测 u 0 ∈ 𝒟 ( F ) {u_{0}inmathcal{D}(F)} 的精确解 u † {u^{dagger}} 时的弗雷谢特导数。 F ′ ( u 0 )∗ {F^{prime}(u_{0})^{ast}} 是 F ′ ( u 0 ) {F^{prime}(u_{0})} 的矢量,{ α n } 是 F ′ ( u 0 ) {F^{prime}(u_{0})} 的矢量。 {{α_{n}}}是一个先验选择的非负实数序列,满足适当的属性。我们使用莫罗佐夫型停止规则来终止迭代。在算子 F 的适当非线性条件下,我们证明了该方法的收敛性,并在元素 u 0 - u † {u_{0}-u^{dagger}} 的荷尔德型源条件下获得了收敛率结果。 .此外,我们还推导出在不使用源条件的情况下方法的收敛性,研究最后通过数值示例验证了理论结论。
{"title":"Error estimates for simplified Levenberg–Marquardt method for nonlinear ill-posed operator equations in Hilbert Spaces","authors":"Pallavi Mahale, Ankush Kumar","doi":"10.1515/jiip-2023-0090","DOIUrl":"https://doi.org/10.1515/jiip-2023-0090","url":null,"abstract":"In this paper, we consider the simplified Levenberg–Marquardt method for nonlinear ill-posed inverse problems in Hilbert spaces for obtaining stable approximations of solutions to the ill-posed nonlinear equations of the form <jats:inline-formula> <jats:alternatives> <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mrow> <m:mrow> <m:mi>F</m:mi> <m:mo></m:mo> <m:mrow> <m:mo stretchy=\"false\">(</m:mo> <m:mi>u</m:mi> <m:mo stretchy=\"false\">)</m:mo> </m:mrow> </m:mrow> <m:mo>=</m:mo> <m:mi>y</m:mi> </m:mrow> </m:math> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_jiip-2023-0090_eq_0323.png\"/> <jats:tex-math>{F(u)=y}</jats:tex-math> </jats:alternatives> </jats:inline-formula>, where <jats:inline-formula> <jats:alternatives> <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mrow> <m:mi>F</m:mi> <m:mo>:</m:mo> <m:mrow> <m:mrow> <m:mi mathvariant=\"script\">𝒟</m:mi> <m:mo></m:mo> <m:mrow> <m:mo stretchy=\"false\">(</m:mo> <m:mi>F</m:mi> <m:mo stretchy=\"false\">)</m:mo> </m:mrow> </m:mrow> <m:mo>⊂</m:mo> <m:mi>𝖴</m:mi> <m:mo>→</m:mo> <m:mi>𝖸</m:mi> </m:mrow> </m:mrow> </m:math> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_jiip-2023-0090_eq_0325.png\"/> <jats:tex-math>{F:mathcal{D}(F)subsetmathsf{U}tomathsf{Y}}</jats:tex-math> </jats:alternatives> </jats:inline-formula> is a nonlinear operator between Hilbert spaces <jats:inline-formula> <jats:alternatives> <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi>𝖴</m:mi> </m:math> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_jiip-2023-0090_eq_0402.png\"/> <jats:tex-math>{mathsf{U}}</jats:tex-math> </jats:alternatives> </jats:inline-formula> and <jats:inline-formula> <jats:alternatives> <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mi>𝖸</m:mi> </m:math> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_jiip-2023-0090_eq_0403.png\"/> <jats:tex-math>{mathsf{Y}}</jats:tex-math> </jats:alternatives> </jats:inline-formula>. The method is defined as follows: <jats:disp-formula> <jats:alternatives> <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mrow> <m:mrow> <m:msubsup> <m:mi>u</m:mi> <m:mrow> <m:mi>n</m:mi> <m:mo>+</m:mo> <m:mn>1</m:mn> </m:mrow> <m:mi>δ</m:mi> </m:msubsup> <m:mo>=</m:mo> <m:mrow> <m:msubsup> <m:mi>u</m:mi> <m:mi>n</m:mi> <m:mi>δ</m:mi> </m:msubsup> <m:mo>-</m:mo> <m:mrow> <m:msup> <m:mrow> <m:mo stretchy=\"false\">(</m:mo> <m:mrow> <m:mrow> <m:msubsup> <m:mi>T</m:mi> <m:mn>0</m:mn> <m:mo>∗</m:mo> </m:msubsup> <m:mo></m:mo> <m:msub> <m:mi>T</m:mi> <m:mn>0</m:mn> </m:msub> </m:mrow> <m:mo>+</m:mo> <m:mrow> <m:msub> <m:mi>α</m:mi> <m:mi>n</m:mi> </m:msub> <m:mo></m:mo> <m:mi>I</m:mi> </m:mrow> </m:mrow> <m:mo stretchy=\"false\">)</m:mo> </m:mrow> <m:mrow> <m:mo>-</m:mo> <m:mn>1</m:mn> </m:mrow> </m:msup> <m:mo></m:mo> <m:msubsup> <m:mi>T</m:mi> <m:mn>0</m:mn> <m:mo>∗</m:mo> </m:msubsup> <m:mo></m:mo> <m:m","PeriodicalId":50171,"journal":{"name":"Journal of Inverse and Ill-Posed Problems","volume":"57 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141531792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We consider an ensemble Kalman inversion scheme for inverse elastic scattering problems in which the unknown quantity is the shape of the scatterer. Assume that the scatterer is a piecewise constant function with known value inside inhomogeneities. The level set method is described as an implicit representation of the scatterer boundary, with Gaussian random fields serving as prior to provide information on the level set functions. The ensemble Kalman filter method is then employed based on the level set functions to reconstruct the shape of the scatterer. We demonstrate the effectiveness of the proposed method using several numerical examples.
{"title":"Ensemble Kalman inversion based on level set method for inverse elastic scattering problem","authors":"Jiangfeng Huang, Quanfeng Wang, Zhaoxing Li","doi":"10.1515/jiip-2023-0060","DOIUrl":"https://doi.org/10.1515/jiip-2023-0060","url":null,"abstract":"We consider an ensemble Kalman inversion scheme for inverse elastic scattering problems in which the unknown quantity is the shape of the scatterer. Assume that the scatterer is a piecewise constant function with known value inside inhomogeneities. The level set method is described as an implicit representation of the scatterer boundary, with Gaussian random fields serving as prior to provide information on the level set functions. The ensemble Kalman filter method is then employed based on the level set functions to reconstruct the shape of the scatterer. We demonstrate the effectiveness of the proposed method using several numerical examples.","PeriodicalId":50171,"journal":{"name":"Journal of Inverse and Ill-Posed Problems","volume":"344 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A controlled system of differential equations under the action of an unknown disturbance is considered. The problem discussed in the paper consists in constructing algorithms for forming a control that provides the realization of a prescribed motion for any admissible disturbance. Namely these algorithms should provide the closeness in the metric of the space of differentiable functions of a phase trajectory of a given controlled system and some etalon trajectory of an analogous system functioning when any outer actions are absent. As the space of admissible disturbances, we take the space of measurable square integrable (with respect to the Euclidean norm) functions. The cases of inaccurate measurements of phase trajectories of both systems at all times and at discrete times are under study. Two computer oriented algorithms for solving the problem are designed. The algorithms are based on the (well-known in the theory of guaranteed control) method of extremal shift. In the process, its local (at each time of control correction) regularization is performed by the method of smoothing functional (the Tikhonov method). In addition, estimates for algorithm’s convergence rate are presented.
{"title":"Application of locally regularized extremal shift to the problem of realization of a prescribed motion","authors":"Yury S. Osipov, Vyacheslav I. Maksimov","doi":"10.1515/jiip-2024-0018","DOIUrl":"https://doi.org/10.1515/jiip-2024-0018","url":null,"abstract":"A controlled system of differential equations under the action of an unknown disturbance is considered. The problem discussed in the paper consists in constructing algorithms for forming a control that provides the realization of a prescribed motion for any admissible disturbance. Namely these algorithms should provide the closeness in the metric of the space of differentiable functions of a phase trajectory of a given controlled system and some etalon trajectory of an analogous system functioning when any outer actions are absent. As the space of admissible disturbances, we take the space of measurable square integrable (with respect to the Euclidean norm) functions. The cases of inaccurate measurements of phase trajectories of both systems at all times and at discrete times are under study. Two computer oriented algorithms for solving the problem are designed. The algorithms are based on the (well-known in the theory of guaranteed control) method of extremal shift. In the process, its local (at each time of control correction) regularization is performed by the method of smoothing functional (the Tikhonov method). In addition, estimates for algorithm’s convergence rate are presented.","PeriodicalId":50171,"journal":{"name":"Journal of Inverse and Ill-Posed Problems","volume":"9 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-15eCollection Date: 2024-01-01DOI: 10.47895/amp.vi0.6712
Clarisse Veronica L Mirhan, Cecile C Dungog, Karen Cybelle J Sotalbo
We report the case of a 33-week-old female fetus born with craniorachischisis to a gravida 5, para 4 (3104) mother with no previous history of conceiving a child with a neural tube defect. Craniorachischisis is characterized by anencephaly and an open defect extending from the brain to the spine and is the most severe and fatal type of neural tube defect. Although the cause of neural tube defects is hypothesized to be multifactorial and is usually sporadic, the risk is increased in neonates born to mothers with a family history or a previous pregnancy with neural tube defect, both of which are not present in the index case. This case is unique in that only during the fifth pregnancy did the couple conceive a child with a neural tube defect, emphasizing that folic acid supplementation, the sole preventive measure proven to decrease the risk of neural tube defects, remains to be important in the periconceptual period for all women of childbearing age.
{"title":"Craniorachischisis in a 33-week-old Female Fetus: A Case Report.","authors":"Clarisse Veronica L Mirhan, Cecile C Dungog, Karen Cybelle J Sotalbo","doi":"10.47895/amp.vi0.6712","DOIUrl":"10.47895/amp.vi0.6712","url":null,"abstract":"<p><p>We report the case of a 33-week-old female fetus born with craniorachischisis to a gravida 5, para 4 (3104) mother with no previous history of conceiving a child with a neural tube defect. Craniorachischisis is characterized by anencephaly and an open defect extending from the brain to the spine and is the most severe and fatal type of neural tube defect. Although the cause of neural tube defects is hypothesized to be multifactorial and is usually sporadic, the risk is increased in neonates born to mothers with a family history or a previous pregnancy with neural tube defect, both of which are not present in the index case. This case is unique in that only during the fifth pregnancy did the couple conceive a child with a neural tube defect, emphasizing that folic acid supplementation, the sole preventive measure proven to decrease the risk of neural tube defects, remains to be important in the periconceptual period for all women of childbearing age.</p>","PeriodicalId":50171,"journal":{"name":"Journal of Inverse and Ill-Posed Problems","volume":"31 1","pages":"74-78"},"PeriodicalIF":0.0,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11151135/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70461370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We investigate a time-dependent inverse source problem for a parabolic partial differential equation with an integral constraint and subject to Neumann boundary conditions in a domain of Rdmathbb{R}^{d}, d≥1dgeq 1. We prove the well-posedness as well as higher regularity of solutions in Hölder spaces. We then develop and implement an algorithm that we use to approximate solutions of the inverse problem by means of a finite element discretization in space. Due to instability in inverse problems, we apply Tikhonov regularization combined with the discrepancy principle for selecting the regularization parameter in order to obtain a stable reconstruction. Our numerical results show that the proposed scheme is an accurate technique for approximating solutions of this inverse problem.
我们研究了在 R d mathbb{R}^{d}, d ≥ 1 dgeq 1 的域中,具有积分约束条件并受诺伊曼边界条件限制的抛物线偏微分方程的时变反源问题。我们证明了在赫尔德空间中解的可求性及高正则性。然后,我们开发并实现了一种算法,通过有限元空间离散化来近似求解逆问题。由于逆问题的不稳定性,我们采用提霍诺夫正则化结合差异原则来选择正则化参数,以获得稳定的重构。我们的数值结果表明,所提出的方案是近似求解该逆问题的精确技术。
{"title":"Well-posedness and Tikhonov regularization of an inverse source problem for a parabolic equation with an integral constraint","authors":"Sedar Ngoma","doi":"10.1515/jiip-2023-0050","DOIUrl":"https://doi.org/10.1515/jiip-2023-0050","url":null,"abstract":"We investigate a time-dependent inverse source problem for a parabolic partial differential equation with an integral constraint and subject to Neumann boundary conditions in a domain of <jats:inline-formula> <jats:alternatives> <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:msup> <m:mi mathvariant=\"double-struck\">R</m:mi> <m:mi>d</m:mi> </m:msup> </m:math> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_jiip-2023-0050_ineq_0001.png\" /> <jats:tex-math>mathbb{R}^{d}</jats:tex-math> </jats:alternatives> </jats:inline-formula>, <jats:inline-formula> <jats:alternatives> <m:math xmlns:m=\"http://www.w3.org/1998/Math/MathML\"> <m:mrow> <m:mi>d</m:mi> <m:mo>≥</m:mo> <m:mn>1</m:mn> </m:mrow> </m:math> <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_jiip-2023-0050_ineq_0002.png\" /> <jats:tex-math>dgeq 1</jats:tex-math> </jats:alternatives> </jats:inline-formula>. We prove the well-posedness as well as higher regularity of solutions in Hölder spaces. We then develop and implement an algorithm that we use to approximate solutions of the inverse problem by means of a finite element discretization in space. Due to instability in inverse problems, we apply Tikhonov regularization combined with the discrepancy principle for selecting the regularization parameter in order to obtain a stable reconstruction. Our numerical results show that the proposed scheme is an accurate technique for approximating solutions of this inverse problem.","PeriodicalId":50171,"journal":{"name":"Journal of Inverse and Ill-Posed Problems","volume":"5 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140576025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we consider a Bayesian method for nonlinear elastic inverse problems. As a working model, we are interested in the inverse problem of restoring elastic properties from measured tissue displacement. In order to reduce the computational cost, we will use the following multi-fidelity model approach. First, we construct a surrogate low-fidelity DNNs-based model in the prior distribution, then use a certain number of simulations of high fidelity model associated with an adaptive strategy online to update the low-fidelity model locally. Numerical examples show that the proposed method can solve nonlinear elastic inverse problems efficiently and accurately.
{"title":"Adaptive neural network surrogate model for solving the nonlinear elastic inverse problem via Bayesian inference","authors":"Fuchang Huo, Kai Zhang, Yu Gao, Jingzhi Li","doi":"10.1515/jiip-2022-0050","DOIUrl":"https://doi.org/10.1515/jiip-2022-0050","url":null,"abstract":"In this paper, we consider a Bayesian method for nonlinear elastic inverse problems. As a working model, we are interested in the inverse problem of restoring elastic properties from measured tissue displacement. In order to reduce the computational cost, we will use the following multi-fidelity model approach. First, we construct a surrogate low-fidelity DNNs-based model in the prior distribution, then use a certain number of simulations of high fidelity model associated with an adaptive strategy online to update the low-fidelity model locally. Numerical examples show that the proposed method can solve nonlinear elastic inverse problems efficiently and accurately.","PeriodicalId":50171,"journal":{"name":"Journal of Inverse and Ill-Posed Problems","volume":"73 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140299177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents classification and analysis of the mathematical models of the spread of COVID-19 in different groups of population such as family, school, office (3–100 people), town (100–5000 people), city, region (0.5–15 million people), country, continent, and the world. The classification covers major types of models (time-series, differential, imitation ones, neural networks models and their combinations). The time-series models are based on analysis of time series using filtration, regression and network methods. The differential models are those derived from systems of ordinary and stochastic differential equations as well as partial differential equations. The imitation models include cellular automata and agent-based models. The fourth group in the classification consists of combinations of nonlinear Markov chains and optimal control theory, derived by methods of the mean-field game theory. COVID-19 is a novel and complicated disease, and the parameters of most models are, as a rule, unknown and estimated by solving inverse problems. The paper contains an analysis of major algorithms of solving inverse problems: stochastic optimization, nature-inspired algorithms (genetic, differential evolution, particle swarm, etc.), assimilation methods, big-data analysis, and machine learning.
{"title":"Artificial intelligence for COVID-19 spread modeling","authors":"Olga Krivorotko, Sergey Kabanikhin","doi":"10.1515/jiip-2024-0013","DOIUrl":"https://doi.org/10.1515/jiip-2024-0013","url":null,"abstract":"This paper presents classification and analysis of the mathematical models of the spread of COVID-19 in different groups of population such as family, school, office (3–100 people), town (100–5000 people), city, region (0.5–15 million people), country, continent, and the world. The classification covers major types of models (time-series, differential, imitation ones, neural networks models and their combinations). The time-series models are based on analysis of time series using filtration, regression and network methods. The differential models are those derived from systems of ordinary and stochastic differential equations as well as partial differential equations. The imitation models include cellular automata and agent-based models. The fourth group in the classification consists of combinations of nonlinear Markov chains and optimal control theory, derived by methods of the mean-field game theory. COVID-19 is a novel and complicated disease, and the parameters of most models are, as a rule, unknown and estimated by solving inverse problems. The paper contains an analysis of major algorithms of solving inverse problems: stochastic optimization, nature-inspired algorithms (genetic, differential evolution, particle swarm, etc.), assimilation methods, big-data analysis, and machine learning.","PeriodicalId":50171,"journal":{"name":"Journal of Inverse and Ill-Posed Problems","volume":"24 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140169017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The second-order mean field games system (MFGS) in a bounded domain with the lateral Cauchy data are considered. This means that both Dirichlet and Neumann boundary data for the solution of the MFGS are given. Two Hölder stability estimates for two slightly different cases are derived. These estimates indicate how stable the solution of the MFGS is with respect to the possible noise in the lateral Cauchy data. Our stability estimates imply uniqueness. The key mathematical apparatus is the apparatus of two new Carleman estimates.
{"title":"On the mean field games system with lateral Cauchy data via Carleman estimates","authors":"Michael V. Klibanov, Jingzhi Li, Hongyu Liu","doi":"10.1515/jiip-2023-0089","DOIUrl":"https://doi.org/10.1515/jiip-2023-0089","url":null,"abstract":"The second-order mean field games system (MFGS) in a bounded domain with the lateral Cauchy data are considered. This means that both Dirichlet and Neumann boundary data for the solution of the MFGS are given. Two Hölder stability estimates for two slightly different cases are derived. These estimates indicate how stable the solution of the MFGS is with respect to the possible noise in the lateral Cauchy data. Our stability estimates imply uniqueness. The key mathematical apparatus is the apparatus of two new Carleman estimates.","PeriodicalId":50171,"journal":{"name":"Journal of Inverse and Ill-Posed Problems","volume":"87 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139657085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}