On stochastic elliptic equations driven by Wiener process with non-local condition

Tuấn, Nguyễn Huy; Hải, Nguyễn Minh; Thach, Tran Ngoc; Can, Nguyen Huu

doi:10.3934/dcdss.2022187

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2023

2024

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Cited by 5 publications

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“…Regularization techniques can also prevent over fitting, which occurs when the model learns too much from the training data and fails to generalize well to new data. In this topic of regularization, many authors have been concerned about the regularization of the ill-posed problem such as Tuan, Thach, Can [17][18][19]. Total variation denoising, which minimizes a functional that consists of a data fidelity term and a total variation term.…”

Section: Introductionmentioning

confidence: 99%

Application of fast Fourier transform method to ill-posed problem in image processing

2023

EJS

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In this work, we focus on investigating ill-posed problems (according to the definition given by Hadamard) in the topic of its application. Specifically, we present some theories about the properties of the ill-posed problem in image processing. By using discrete Fourier transform and fast Fourier transform methods, we present several results on image processing topic. Finally, some illustrative examples are presented through algorithms running on Python software.

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Section: Introductionmentioning

confidence: 99%