In this paper, we study the inverse problem of identifying the parameters in a nonlinear
subdiffusion model from an observation defined in the given Ω1 subset of Ω. The nonlinear …

The alternating direction method of multipliers within a shape optimization framework is
developed for solving geometric inverse problems, focusing on a cavity identification …

The paper deals with an inverse problem of identifying parameters in a nonlinear
subdiffusion model from a final observation. The nonlinear subdiffusion model involves a …

An estimation for the unknown source term in the time-fractional diffusion equation from
measurement data by the alternating direction method of multipliers (ADMM) is considered …

This research introduces an enhanced approach for multiframe super-resolution (SR) that
incorporates a bilevel optimization technique for learning the space variable weights …

In this paper, we aim to study an inverse problem for determining two time-independent
coefficients in a fractional diffusion system from the final measurements. First, we prove the …

In this paper, we introduce a deep learning neural network approach to precisely identify
space-dependent diffusion coefficients within a time-fractional diffusion equation by …

In this study, we address an inverse problem in nonlinear time-fractional diffusion equations
using a deep neural network. The challenge arises from the equation's nonlinear behavior …

A determination of the nonsmooth potential parameter in a nonlinear subdiffusion model
using terminal observation through a nonsmooth optimal control approach is proposed. This …

This paper is concerned with analyzing a nonlocal inverse problem that arises within the
field of image processing. The proposed model is governed by a nonlocal Weickert diffusion …