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This work is devoted to designing a unified alternating update method for solving a class of structured low rank approximations under the convex and unitarily invariant norm.
We introduce in this paper fixed-point proximity-gradient algorithms for solving a class of structured convex optimization problems arising from image restoration.
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Mathematical programming is an art that provides precise techniques for solving a class of problems.
This algorithm was employed for solving a class of variable-order fractional differential equations.
Each shape describes a class of structures, and within each class, the structure of minimum free energy is defined as the shape representative structure, called shrep for short.
Stochastic, zero-order, population-based optimization methods are ideal for solving this class of problems.
In this paper, a novel neural network design algorithm is presented for solving multi-class problems, structure decomposition based on Skeletonization (SDBSkeletonization), which is to simplify NNs further.
Finally, we suggest the most appropriate algorithms for solving different classes of PSP problem.
Multisymplectic (MS) integrators, i.e. numerical schemes which exactly preserve a discrete space time symplectic structure, are a new class of structure preserving algorithms for solving Hamiltonian PDEs.
This approach is a special case of using output codes for solving multi class problems [42].
This paper presents a new design of adaptive fuzzy variable structure control to solve the traditional problem of model reference adaptive control (MRAC) for a class of single-input, single-output minimum-phase uncertain nonlinear systems via backstepping.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com