A locally quadratically convergent method of constrained minimization using a modified Lagrangian

1980 ◽  
Vol 20 (1) ◽  
pp. 28-40
Author(s):  
G.D. Maistrovskii
Keyword(s):  
Constrained Minimization ◽  
Convergent Method

scholarly journals A Projected Forward-Backward Algorithm for Constrained Minimization with Applications to Image Inpainting

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 890
Author(s):  
Suthep Suantai ◽  
Kunrada Kankam ◽  
Prasit Cholamjiak
Keyword(s):  
Image Processing ◽  
Minimization Problem ◽  
Convex Functions ◽  
Lower Semicontinuous ◽  
Image Inpainting ◽  
Constrained Minimization ◽  
Convex Minimization Problem ◽  
Mild Conditions ◽  
Constrained Minimization Problem ◽  
Weak Convergence Theorem

In this research, we study the convex minimization problem in the form of the sum of two proper, lower-semicontinuous, and convex functions. We introduce a new projected forward-backward algorithm using linesearch and inertial techniques. We then establish a weak convergence theorem under mild conditions. It is known that image processing such as inpainting problems can be modeled as the constrained minimization problem of the sum of convex functions. In this connection, we aim to apply the suggested method for solving image inpainting. We also give some comparisons to other methods in the literature. It is shown that the proposed algorithm outperforms others in terms of iterations. Finally, we give an analysis on parameters that are assumed in our hypothesis.

Convexity of a discrete Carleman weighted objective functional in an inverse medium scattering problem

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Nguyen Trung Thành
Keyword(s):  
Finite Number ◽  
Scattering Problem ◽  
One Dimensional ◽  
Globally Convergent ◽  
Convergent Method ◽  
Inverse Medium ◽  
Inverse Medium Scattering ◽  
Objective Functional

AbstractWe investigate a globally convergent method for solving a one-dimensional inverse medium scattering problem using backscattering data at a finite number of frequencies. The proposed method is based on the minimization of a discrete Carleman weighted objective functional. The global convexity of this objective functional is proved.

scholarly journals A derivative free globally convergent method and its deformations

2021 ◽  
Author(s):  
Manoj Kumar Singh ◽  
Arvind K. Singh
Keyword(s):  
Difference Operator ◽  
Linear Equations ◽  
Numerical Test ◽  
Test Functions ◽  
Globally Convergent ◽  
Forward Difference ◽  
Derivative Free ◽  
Fractal Patterns ◽  
Convergent Method ◽  
Non Linear Equations

AbstractThe motive of the present work is to introduce and investigate the quadratically convergent Newton’s like method for solving the non-linear equations. We have studied some new properties of a Newton’s like method with examples and obtained a derivative-free globally convergent Newton’s like method using forward difference operator and bisection method. Finally, we have used various numerical test functions along with their fractal patterns to show the utility of the proposed method. These patterns support the numerical results and explain the compactness regarding the convergence, divergence and stability of the methods to different roots.

ChemInform Abstract: Photocycloaddition of Phthalimide Anion to Alkenes - A Highly Efficient, Convergent Method for [2]Benzazepine Synthesis.

ChemInform ◽  
2010 ◽  
Vol 33 (40) ◽  
pp. no-no
Author(s):  
Rafael Suau ◽  
Cristobal Sanchez-Sanchez ◽  
Rafael Garcia-Segura ◽  
Ezequiel Perez-Inestrosa
Keyword(s):  
Highly Efficient ◽  
Convergent Method
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