Search
Search Results
-
A Nonmonotone Scaled Fletcher–Reeves Conjugate Gradient Method with Application in Image Reconstruction
In an effort to make modification on the classical Fletcher–Reeves method, Jiang and Jian suggested an efficient nonlinear conjugate gradient...
-
Learned Iterative Reconstruction
Learned iterative reconstruction methods have recently emerged as a powerful tool to solve inverse problems. These deep learning techniques for image...
-
Scalable enforcement of geometric non-interference constraints for gradient-based optimization
Many design optimization problems include constraints to prevent intersection of the geometric shape being optimized with other objects or with...
-
Gradient Robust Mixed Methods for Nearly Incompressible Elasticity
Within the last years pressure robust methods for the discretization of incompressible fluids have been developed. These methods allow the use of...
-
Smoothing Strategy Along with Conjugate Gradient Algorithm for Signal Reconstruction
In this paper, we propose a new smoothing strategy along with conjugate gradient algorithm for the signal reconstruction problem. Theoretically, the...
-
Numerical Reconstruction of a Discontinuous Diffusive Coefficient in Variable-Order Time-Fractional Subdiffusion
We consider a discontinuous coefficient reconstruction problem associated with a variable-order time-fractional subdiffusion equation. Both interface...
-
Discontinuity Detection by Null Rules for Adaptive Surface Reconstruction
We present a discontinuity detection method based on the so-called null rules, computed as a vector in the null space of certain collocation...
-
Pressure Reconstruction
This chapter is concerned with the reconstruction of the scalar kinematice pressure in an appropriate function space, which will show that the...
-
Template-Based Image Reconstruction Facing Different Topologies
The reconstruction of images from measured data is an increasing field of research. For highly under-determined problems, template-based image...
-
Enhancing Electrical Impedance Tomography Reconstruction Using Learned Half-Quadratic Splitting Networks with Anderson Acceleration
Electrical Impedance Tomography (EIT) is widely applied in medical diagnosis, industrial inspection, and environmental monitoring. Combining the...
-
Gradient-Based Monte Carlo Methods for Relaxation Approximations of Hyperbolic Conservation Laws
Particle methods based on evolving the spatial derivatives of the solution were originally introduced to simulate reaction-diffusion processes,...
-
Accelerated Sparse Recovery via Gradient Descent with Nonlinear Conjugate Gradient Momentum
This paper applies an idea of adaptive momentum for the nonlinear conjugate gradient to accelerate optimization problems in sparse recovery....
-
Gradient-Robust Hybrid DG Discretizations for the Compressible Stokes Equations
This paper studies two hybrid discontinuous Galerkin (HDG) discretizations for the velocity-density formulation of the compressible Stokes equations...
-
Convergent Data-Driven Regularizations for CT Reconstruction
The reconstruction of images from their corresponding noisy Radon transform is a typical example of an ill-posed linear inverse problem as arising in...
-
A Posteriori Error Estimates and Adaptive Error Control for Permittivity Reconstruction in Conductive Media
An inverse problem of reconstruction of the spatially distributed dielectric permittivity function in the Maxwell’s system is considered. The...
-
Gradient-based algorithms for multi-objective bi-level optimization
Multi-objective bi-level optimization (MOBLO) addresses nested multi-objective optimization problems common in a range of applications. However, its...
-
Sound field reconstruction using improved ℓ1-norm and the Cauchy penalty method
Automotive noise source identification is important for improving driving comfort and protecting people’s auditory health. However, the stable,...
-
An improved spectral conjugate gradient projection method for monotone nonlinear equations with application
In this paper, we propose an enhanced spectral conjugate gradient (CG) projection method for solving monotone nonlinear equations with application in...
-
Scaled Proximal Gradient Methods for Sparse Optimization Problems
Thresholding-based methods are widely used for sparse optimization problems in many applications including compressive sensing, image processing, and...
-
Diffraction Tomography, Fourier Reconstruction, and Full Waveform Inversion
In this chapter, we study the mathematical imaging problem of diffraction tomography (DT), which is an inverse scattering technique used to find...