Comparison of steepest descent method and conjugate gradient method

Oleksandra Osadcha; Zbigniew Marszaek

Comparison of steepest descent method and conjugate gradient method

Oleksandra Osadcha
, Zbigniew Marszaek

Katedra Modelowania Sztucznej Inteligencji (RMS/RMS2)

Silesian University of Technology

Wyniki badań: Wkład do czasopisma › Artykuł z konferencji › recenzja

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Abstrakt

This paper illustrates comparison of two methods, which are used for solving systems of linear equations. The aim of the research is to analyze, which method is faster solve this equations and how many iteration required each method for solving. This paper presents some ways to deal with this problem. Also there are analyzed two methods. The first of them minimizes the standard deviation of the next iteration of the solution, the other constructs orthogonal vectors and is theoretically finite method.

Język oryginału	angielski
Strony (od–do)	1-4
Liczba stron	4
Czasopismo	CEUR Workshop Proceedings
Tom	1853
Status publikacji	Opublikowano - 2017
Wydarzenie	2017 Symposium for Young Scientists in Technology, Engineering and Mathematics, SYSTEM 2017 - Kaunas, Litwa Czas trwania: 28 kwi 2017 → …

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Cytowanie

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abstract = "This paper illustrates comparison of two methods, which are used for solving systems of linear equations. The aim of the research is to analyze, which method is faster solve this equations and how many iteration required each method for solving. This paper presents some ways to deal with this problem. Also there are analyzed two methods. The first of them minimizes the standard deviation of the next iteration of the solution, the other constructs orthogonal vectors and is theoretically finite method.",

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AU - Osadcha, Oleksandra

AU - Marszaek, Zbigniew

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N2 - This paper illustrates comparison of two methods, which are used for solving systems of linear equations. The aim of the research is to analyze, which method is faster solve this equations and how many iteration required each method for solving. This paper presents some ways to deal with this problem. Also there are analyzed two methods. The first of them minimizes the standard deviation of the next iteration of the solution, the other constructs orthogonal vectors and is theoretically finite method.

AB - This paper illustrates comparison of two methods, which are used for solving systems of linear equations. The aim of the research is to analyze, which method is faster solve this equations and how many iteration required each method for solving. This paper presents some ways to deal with this problem. Also there are analyzed two methods. The first of them minimizes the standard deviation of the next iteration of the solution, the other constructs orthogonal vectors and is theoretically finite method.

KW - Analysis

KW - Comparison

KW - Conjugate gradient method

KW - Steepest descent method

UR - https://www.scopus.com/pages/publications/85021114730

M3 - Conference article

AN - SCOPUS:85021114730

SN - 1613-0073

VL - 1853

SP - 1

EP - 4

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

T2 - 2017 Symposium for Young Scientists in Technology, Engineering and Mathematics, SYSTEM 2017

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ER -

Comparison of steepest descent method and conjugate gradient method

Abstrakt

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