INVERSE BOUNDARY VALUE PROBLEM

Авторы

  • Muzaffar Sulaymonovich Azizov Автор
  • Odina Isroiljon qizi Ismoiljonova Автор

Ключевые слова:

Gradient method, steepest descent, iterative method, symmetric matrix, positive definiteness, functional, optimization, Python, algorithm, error vector.

Аннотация

This article discusses the steepest descent algorithm of the gradient method used to solve systems of linear algebraic equations. The method for finding the solution by minimizing a functional is explained step-by-step. Theoretical foundations 
based on gradient and error vectors are presented. A practical example involving a system of four equations is solved using Python, and the convergence rate and accuracy of the algorithm are demonstrated. The results show that the gradient method is a 
simple and efficient computational tool suitable for solving large-scale linear systems. 

Библиографические ссылки

1.

Lavrentyev, M.M., Romanov, V.G., Yanyushkin, S.P. – Obratnye

zadachi matematicheskoy fiziki. Moscow: Nauka, 1986.

2.

Tikhonov, A.N., Arsenin, V.Y. – Reshenie nekorrektnykh zadach.

Moscow: Nauka, 1979.

3.

Isakov, V. – Inverse Problems for Partial Differential Equations.

Springer, 2006.

4.

Wesley, 1984.

5.

Cannon, J.M. – The One-Dimensional Heat Equation. Addison

Aliev, N.A. – Introduction to the Theory of Inverse Problems.

Tashkent: Fan, 1998.

6.

Mukhamedov, A.K. – Equations of Mathematical Physics and Their

Inverse Problems. Fergana: FSU Publishing, 2022.

7.

Rasskazov, A.V. – Theoretical Foundations of Methods for Solving

Inverse Problems. Novosibirsk, 2001.

Опубликован

2025-05-18

Как цитировать

INVERSE BOUNDARY VALUE PROBLEM . (2025). ОБРАЗОВАНИЕ НАУКА И ИННОВАЦИОННЫЕ ИДЕИ В МИРЕ, 69(4), 444-450. https://scientific-jl.com/obr/article/view/14341