Differential Equations and Inverse Problems

A special issue of Axioms (ISSN 2075-1680). This special issue belongs to the section "Mathematical Analysis".

Deadline for manuscript submissions: closed (28 August 2024) | Viewed by 12545

Special Issue Editors

College of Sciences, Northeastern University, Shenyang 110819, China
Interests: deep learning; reinforcement learning; multiscale methods (multigrid and wavelet); homotopy method; inverse and Ill-posed problems; parameter reconstruction
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Guest Editor
Department of Mathematics, Harbin Institute of Technology, Harbin 150001, China
Interests: structure-preserving algorithms for differential equations; numerical methods for stochastic differential equation
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Guest Editor
School of Mathematics and Statistics, Northeastern University at Qinhuangdao, Qinhuangdao, China
Interests: ill-posed problems; regularization method; inverse source problems; backward problems; parabolic equation; elliptic equation; fractional diffusion equation; convergence analysis

Special Issue Information

Dear Colleagues,

Differential equations and inverse problems have become a rapidly growing topic because of the new techniques developed recently and amazing achievements in computational sciences. With the progress of science and technology, differential equations and inverse problems have quickly developed, and new waves have been successively set off in a broad range of disciplines, such as mathematics, physics, engineering, business, economics, earth science, biology, etc. 

The purpose of this Special Issue is to gather contributions from experts on the theory and numerical aspects of differential equations and inverse problems, including but not limited to differential equations and fractional differential equations, initial value problems and related inverse problems, boundary value problems and related inverse problems, inverse problems in imaging, image reconstruction in tomography, stability analysis, regularization methods, novel numerical algorithms (such as multigrid methods, wavelet methods, homotopy methods, structure-preserving methods), and artificial intelligence (such as deep learning, reinforcement learning). Moreover, we encourage submissions of their applications in various practical areas. 

Dr. Tao Liu
Dr. Qiang Ma
Dr. Songshu Liu
Guest Editors

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Keywords

  • partial differential equations
  • ordinary differential equations
  • stochastic differential equations
  • fractional differential equations
  • fractional calculus
  • inverse and ill-posed problems
  • imaging
  • image reconstruction
  • tomography
  • tomographic reconstruction
  • regularization methods
  • numerical methods
  • structure-preserving methods
  • artificial intelligence
  • deep learning
  • reinforcement learning

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Published Papers (12 papers)

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Research

19 pages, 1493 KiB  
Article
An Efficient Anti-Noise Zeroing Neural Network for Time-Varying Matrix Inverse
by Jiaxin Hu, Feixiang Yang and Yun Huang
Axioms 2024, 13(8), 540; https://doi.org/10.3390/axioms13080540 - 9 Aug 2024
Viewed by 438
Abstract
The Time-Varying Matrix Inversion (TVMI) problem is integral to various fields in science and engineering. Countless studies have highlighted the effectiveness of Zeroing Neural Networks (ZNNs) as a dependable approach for addressing this challenge. To effectively solve the TVMI problem, this paper introduces [...] Read more.
The Time-Varying Matrix Inversion (TVMI) problem is integral to various fields in science and engineering. Countless studies have highlighted the effectiveness of Zeroing Neural Networks (ZNNs) as a dependable approach for addressing this challenge. To effectively solve the TVMI problem, this paper introduces a novel Efficient Anti-Noise Zeroing Neural Network (EANZNN). This model employs segmented time-varying parameters and double integral terms, where the segmented time-varying parameters can adaptively adjust over time, offering faster convergence speeds compared to fixed parameters. The double integral term enables the model to effectively handle the interference of constant noise, linear noise, and other noises. Using the Lyapunov approach, we theoretically analyze and show the convergence and robustness of the proposed EANZNN model. Experimental findings showcase that in scenarios involving linear, constant noise and noise-free environments, the EANZNN model exhibits superior performance compared to traditional models like the Double Integral-Enhanced ZNN (DIEZNN) and the Parameter-Changing ZNN (PCZNN). It demonstrates faster convergence and better resistance to interference, affirming its efficacy in addressing TVMI problems. Full article
(This article belongs to the Special Issue Differential Equations and Inverse Problems)
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19 pages, 1282 KiB  
Article
An Accelerated Dual-Integral Structure Zeroing Neural Network Resistant to Linear Noise for Dynamic Complex Matrix Inversion
by Feixiang Yang, Tinglei Wang and Yun Huang
Axioms 2024, 13(6), 374; https://doi.org/10.3390/axioms13060374 - 2 Jun 2024
Cited by 1 | Viewed by 544
Abstract
The problem of inverting dynamic complex matrices remains a central and intricate challenge that has garnered significant attention in scientific and mathematical research. The zeroing neural network (ZNN) has been a notable approach, utilizing time derivatives for real-time solutions in noiseless settings. However, [...] Read more.
The problem of inverting dynamic complex matrices remains a central and intricate challenge that has garnered significant attention in scientific and mathematical research. The zeroing neural network (ZNN) has been a notable approach, utilizing time derivatives for real-time solutions in noiseless settings. However, real-world disturbances pose a significant challenge to a ZNN’s convergence. We design an accelerated dual-integral structure zeroing neural network (ADISZNN), which can enhance convergence and restrict linear noise, particularly in complex domains. Based on the Lyapunov principle, theoretical analysis proves the convergence and robustness of ADISZNN. We have selectively integrated the SBPAF activation function, and through theoretical dissection and comparative experimental validation we have affirmed the efficacy and accuracy of our activation function selection strategy. After conducting numerous experiments, we discovered oscillations and improved the model accordingly, resulting in the ADISZNN-Stable model. This advanced model surpasses current models in both linear noisy and noise-free environments, delivering a more rapid and stable convergence, marking a significant leap forward in the field. Full article
(This article belongs to the Special Issue Differential Equations and Inverse Problems)
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13 pages, 287 KiB  
Article
On the Kantorovich Theory for Nonsingular and Singular Equations
by Ioannis K. Argyros, Santhosh George, Samundra Regmi and Michael I. Argyros
Axioms 2024, 13(6), 358; https://doi.org/10.3390/axioms13060358 - 28 May 2024
Viewed by 531
Abstract
We develop a new Kantorovich-like convergence analysis of Newton-type methods to solve nonsingular and singular nonlinear equations in Banach spaces. The outer or generalized inverses are exchanged by a finite sum of linear operators making the implementation of these methods easier than in [...] Read more.
We develop a new Kantorovich-like convergence analysis of Newton-type methods to solve nonsingular and singular nonlinear equations in Banach spaces. The outer or generalized inverses are exchanged by a finite sum of linear operators making the implementation of these methods easier than in earlier studies. The analysis uses relaxed generalized continuity of the derivatives of operators involved required to control the derivative and on real majorizing sequences. The same approach can also be implemented on other iterative methods with inverses. The examples complement the theory by verifying the convergence conditions and demonstrating the performance of the methods. Full article
(This article belongs to the Special Issue Differential Equations and Inverse Problems)
20 pages, 584 KiB  
Article
New Simplified High-Order Schemes for Solving SDEs with Markovian Switching Driven by Pure Jumps
by Yang Li, Yingmei Xu, Qianhai Xu and Yu Zhang
Axioms 2024, 13(3), 190; https://doi.org/10.3390/axioms13030190 - 13 Mar 2024
Viewed by 1022
Abstract
New high-order weak schemes are proposed and simplified to solve stochastic differential equations with Markovian switching driven by pure jumps (PJ-SDEwMs). Using Malliavin calculus theory, it is rigorously proven that the new numerical schemes can achieve a high-order convergence rate. Some numerical experiments [...] Read more.
New high-order weak schemes are proposed and simplified to solve stochastic differential equations with Markovian switching driven by pure jumps (PJ-SDEwMs). Using Malliavin calculus theory, it is rigorously proven that the new numerical schemes can achieve a high-order convergence rate. Some numerical experiments are provided to show the efficiency and accuracy. Full article
(This article belongs to the Special Issue Differential Equations and Inverse Problems)
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15 pages, 277 KiB  
Article
Solvability Criterion for a System Arising from Monge–Ampère Equations with Two Parameters
by Liangyu Wang and Hongyu Li
Axioms 2024, 13(3), 175; https://doi.org/10.3390/axioms13030175 - 7 Mar 2024
Viewed by 888
Abstract
Monge–Ampère equations have important research significance in many fields such as geometry, convex geometry and mathematical physics. In this paper, under some superlinear and sublinear conditions, the existence of nontrivial solutions for a system arising from Monge–Ampère equations with two parameters is investigated [...] Read more.
Monge–Ampère equations have important research significance in many fields such as geometry, convex geometry and mathematical physics. In this paper, under some superlinear and sublinear conditions, the existence of nontrivial solutions for a system arising from Monge–Ampère equations with two parameters is investigated based on the Guo–Krasnosel’skii fixed point theorem. In the end, two examples are given to illustrate our theoretical results. Full article
(This article belongs to the Special Issue Differential Equations and Inverse Problems)
12 pages, 268 KiB  
Article
On a Backward Problem for the Rayleigh–Stokes Equation with a Fractional Derivative
by Songshu Liu, Tao Liu and Qiang Ma
Axioms 2024, 13(1), 30; https://doi.org/10.3390/axioms13010030 - 30 Dec 2023
Viewed by 1020
Abstract
The Rayleigh–Stokes equation with a fractional derivative is widely used in many fields. In this paper, we consider the inverse initial value problem of the Rayleigh–Stokes equation. Since the problem is ill-posed, we adopt the Tikhonov regularization method to solve this problem. In [...] Read more.
The Rayleigh–Stokes equation with a fractional derivative is widely used in many fields. In this paper, we consider the inverse initial value problem of the Rayleigh–Stokes equation. Since the problem is ill-posed, we adopt the Tikhonov regularization method to solve this problem. In addition, this paper not only analyzes the ill-posedness of the problem but also gives the conditional stability estimate. Finally, the convergence estimates are proved under two regularization parameter selection rules. Full article
(This article belongs to the Special Issue Differential Equations and Inverse Problems)
22 pages, 538 KiB  
Article
Asymptotical Stability Criteria for Exact Solutions and Numerical Solutions of Nonlinear Impulsive Neutral Delay Differential Equations
by Gui-Lai Zhang, Zhi-Wei Wang, Yang Sun and Tao Liu
Axioms 2023, 12(10), 988; https://doi.org/10.3390/axioms12100988 - 18 Oct 2023
Viewed by 1033
Abstract
In this paper, the idea of two transformations is first proposed and applied. Some new different sufficient conditions for the asymptotical stability of the exact solutions of nonlinear impulsive neutral delay differential equations (INDDEs) are obtained. A new numerical scheme for INDDEs is [...] Read more.
In this paper, the idea of two transformations is first proposed and applied. Some new different sufficient conditions for the asymptotical stability of the exact solutions of nonlinear impulsive neutral delay differential equations (INDDEs) are obtained. A new numerical scheme for INDDEs is also constructed based on the idea. The numerical methods that can preserve the stability and asymptotical stability of the exact solutions are provided. Two numerical examples are provided to demonstrate the theoretical results. Full article
(This article belongs to the Special Issue Differential Equations and Inverse Problems)
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15 pages, 337 KiB  
Article
Sinc Collocation Method to Simulate the Fractional Partial Integro-Differential Equation with a Weakly Singular Kernel
by Mingzhu Li, Lijuan Chen and Yongtao Zhou
Axioms 2023, 12(9), 898; https://doi.org/10.3390/axioms12090898 - 21 Sep 2023
Cited by 1 | Viewed by 1025
Abstract
In this article, we develop an efficient numerical scheme for dealing with fractional partial integro-differential equations (FPIEs) with a weakly singular kernel. The weight and shift Grünwald difference (WSGD) operator is adopted to approximate a time fractional derivative and the Sinc collocation method [...] Read more.
In this article, we develop an efficient numerical scheme for dealing with fractional partial integro-differential equations (FPIEs) with a weakly singular kernel. The weight and shift Grünwald difference (WSGD) operator is adopted to approximate a time fractional derivative and the Sinc collocation method is applied for discretizing the spatial derivative.The exponential convergence of our proposed method is demonstrated in detail. Finally, numerical evidence is employed to verify the theoretical results and confirm the expected convergence rate. Full article
(This article belongs to the Special Issue Differential Equations and Inverse Problems)
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14 pages, 3289 KiB  
Article
An Efficient Convolutional Neural Network with Supervised Contrastive Learning for Multi-Target DOA Estimation in Low SNR
by Yingchun Li, Zhengjie Zhou, Cheng Chen, Peng Wu and Zhiquan Zhou
Axioms 2023, 12(9), 862; https://doi.org/10.3390/axioms12090862 - 7 Sep 2023
Cited by 3 | Viewed by 1352
Abstract
In this paper, a modified high-efficiency Convolutional Neural Network (CNN) with a novel Supervised Contrastive Learning (SCL) approach is introduced to estimate direction-of-arrival (DOA) of multiple targets in low signal-to-noise ratio (SNR) regimes with uniform linear arrays (ULA). The model is trained using [...] Read more.
In this paper, a modified high-efficiency Convolutional Neural Network (CNN) with a novel Supervised Contrastive Learning (SCL) approach is introduced to estimate direction-of-arrival (DOA) of multiple targets in low signal-to-noise ratio (SNR) regimes with uniform linear arrays (ULA). The model is trained using an on-grid setting, and thus the problem is modeled as a multi-label classification task. Simulation results demonstrate the robustness of the proposed approach in scenarios with low SNR and a small number of snapshots. Notably, the method exhibits strong capability in detecting the number of sources while estimating their DOAs. Furthermore, compared to traditional CNN methods, our refined efficient CNN significantly reduces the number of parameters by a factor of sixteen while still achieving comparable results. The effectiveness of the proposed method is analyzed through the visualization of latent space and through the advanced theory of feature learning. Full article
(This article belongs to the Special Issue Differential Equations and Inverse Problems)
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13 pages, 304 KiB  
Article
Positive Solutions for Periodic Boundary Value Problems of Fractional Differential Equations with Sign-Changing Nonlinearity and Green’s Function
by Rian Yan and Yige Zhao
Axioms 2023, 12(9), 819; https://doi.org/10.3390/axioms12090819 - 26 Aug 2023
Cited by 3 | Viewed by 918
Abstract
In this paper, a class of nonlinear fractional differential equations with periodic boundary condition is investigated. Although the nonlinearity of the equation and the Green’s function are sign-changing, the results of the existence and nonexistence of positive solutions are obtained by using the [...] Read more.
In this paper, a class of nonlinear fractional differential equations with periodic boundary condition is investigated. Although the nonlinearity of the equation and the Green’s function are sign-changing, the results of the existence and nonexistence of positive solutions are obtained by using the Schaefer’s fixed-point theorem. Finally, two examples are given to illustrate the main results. Full article
(This article belongs to the Special Issue Differential Equations and Inverse Problems)
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14 pages, 2367 KiB  
Article
The Laplace Transform Shortcut Solution to a One-Dimensional Heat Conduction Model with Dirichlet Boundary Conditions
by Dan Wu, Yuezan Tao and Honglei Ren
Axioms 2023, 12(8), 770; https://doi.org/10.3390/axioms12080770 - 9 Aug 2023
Cited by 1 | Viewed by 1749
Abstract
When using the Laplace transform to solve a one-dimensional heat conduction model with Dirichlet boundary conditions, the integration and transformation processes become complex and cumbersome due to the varying properties of the boundary function f(t). Meanwhile, if f(t [...] Read more.
When using the Laplace transform to solve a one-dimensional heat conduction model with Dirichlet boundary conditions, the integration and transformation processes become complex and cumbersome due to the varying properties of the boundary function f(t). Meanwhile, if f(t) has a complex functional form, e.g., an exponential decay function, the product of the image function of the Laplace transform and the general solution to the model cannot be obtained directly due to the difficulty in solving the inverse. To address this issue, operators are introduced to replace f(t) in the transformation process. Based on the properties of the Laplace transform and the convolution theorem, without the direct involvement of f(t) in the transformation, a general theoretical solution incorporating f(t) is derived, which consists of the product of erfc(t) and f(0), as well as the convolution of erfc(t) and the derivative of f(t). Then, by substituting f(t) into the general theoretical solution, the corresponding analytical solution is formulated. Based on the general theoretical solution, analytical solutions are given for f(t) as a commonly used function. Finally, combined with an exemplifying application demonstration based on the test data of temperature T(x, t) at point x away from the boundary and the characteristics of curve T(x, t) − t and curve 𝜕T(x, t)/𝜕tt, the inflection point and curve fitting methods are established for the inversion of model parameters. Full article
(This article belongs to the Special Issue Differential Equations and Inverse Problems)
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14 pages, 327 KiB  
Article
Convergence of Collocation Methods for One Class of Impulsive Delay Differential Equations
by Zhiwei Wang, Guilai Zhang and Yang Sun
Axioms 2023, 12(7), 700; https://doi.org/10.3390/axioms12070700 - 19 Jul 2023
Cited by 2 | Viewed by 939
Abstract
This paper is concerned with collocation methods for one class of impulsive delay differential equations (IDDEs). Some results for the convergence, global superconvergence and local superconvergence of collocation methods are given. We choose a suitable piecewise continuous collocation space to obtain high-order numerical [...] Read more.
This paper is concerned with collocation methods for one class of impulsive delay differential equations (IDDEs). Some results for the convergence, global superconvergence and local superconvergence of collocation methods are given. We choose a suitable piecewise continuous collocation space to obtain high-order numerical methods. Some illustrative examples are given to verify the theoretical results. Full article
(This article belongs to the Special Issue Differential Equations and Inverse Problems)
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