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Method of conjugate subgradients with constrained memoryMethod of conjugate subgradients with constrained memory
Preconditioned iterative methods for a class of nonlinear eigenvalue problems, and preconditioned conjugate gradient method. These methods use only matrix-vector multiplications, preconditioner
Preconditioned iterative methods for a class of nonlinear eigenvalue problems, and preconditioned conjugate gradient method. These methods use only matrix-vector multiplications, preconditioner
ON CALCULATING OF FUNCTIONAL DERIVATIVE FOR AN OPTIMAL CONTROL PROBLEM; [О ВЫЧИСЛЕНИИ ФУНКЦИОНАЛЬНОЙ ПРОИЗВОДНОЙ ДЛЯ ОДНОЙ ЗАДАЧИ ОПТИМАЛЬНОГО УПРАВЛЕНИЯ] of the grating profile. The gradient method is the most reliable and stable method for solving this problem
Positive definiteness of forms: Numerical identification optimization technique, namely, the steepest descent and the conjugate gradient methods. The effectiveness
О вычислении функциональной производной для одной задачи оптимального управления of the grating profile. The gradient method is the most reliable and stable method for solving this problem
Технико-экономическое обоснование выбора места расположения подстанции station with the existing methods and also with conjugate gradient method are designed. The results
Gradient conjugate priors and multi-layer neural networks networks. We suggest a so-called gradient conjugate prior (GCP) update appropriate for neural networks
Checking the definiteness of forms, such as the steepest descent method and the conjugate gradient method. A theoretical analysis and computational
A method for separation of classes of linear conjugation problems for three-dimensional vector of the homogeneouslinear conjugation problems for three-dimensional vector, and study their relations with a system of two
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