Open AccessComparison Between Steepest Descent Method and Conjugate Gradient Method by Using Matlab
Author(s) -
Dana Taha Mohammed Salih,
Bawar Mohammed Faraj
Publication year - 2021
Language(s) - English
DOI - 10.53898/josse2021113
Subject(s) - nonlinear conjugate gradient method , conjugate gradient method , gradient descent , method of steepest descent , derivation of the conjugate gradient method , conjugate residual method , matlab , gradient method , mathematics , mathematical optimization , computer science , artificial neural network , artificial intelligence , operating system
The Steepest descent method and the Conjugate gradient method to minimize nonlinear functions have been studied in this work. Algorithms are presented and implemented in Matlab software for both methods. However, a comparison has been made between the Steepest descent method and the Conjugate gradient method. The obtained results in Matlab software has time and efficiency aspects. It is shown that the Conjugate gradient method needs fewer iterations and has more efficiency than the Steepest descent method. On the other hand, the Steepest descent method converges a function in less time than the Conjugate gradient method.