A Survey of Conjugate Gradient Algorithms for Solution of Extreme Eigen-Problems of a Symmetric Matrix

Xiaopu Yang; Tapan K. Sarkar; Ercument Arvas

doi:10.1109/29.35393

A Survey of Conjugate Gradient Algorithms for Solution of Extreme Eigen-Problems of a Symmetric Matrix

Xiaopu Yang, Tapan K. Sarkar, Ercument Arvas

Department of Electrical Engineering & Computer Science

Research output: Contribution to journal › Article › peer-review

84 Scopus citations

Abstract

A survey of various conjugate gradient (CG) algorithms is presented for the extreme eigen-probiems of a symmetric matrix. The CG algorithms are compared to a commonly used conventional method found in IMSL. It is concluded that the CG algorithms are more flexible and efficient than some of the conventional methods used in adaptive spectrum analysis and signal processing.

Original language	English (US)
Pages (from-to)	1550-1556
Number of pages	7
Journal	IEEE Transactions on Acoustics, Speech, and Signal Processing
Volume	37
Issue number	10
DOIs	https://doi.org/10.1109/29.35393
State	Published - Oct 1989

ASJC Scopus subject areas

Signal Processing

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title = "A Survey of Conjugate Gradient Algorithms for Solution of Extreme Eigen-Problems of a Symmetric Matrix",

abstract = "A survey of various conjugate gradient (CG) algorithms is presented for the extreme eigen-probiems of a symmetric matrix. The CG algorithms are compared to a commonly used conventional method found in IMSL. It is concluded that the CG algorithms are more flexible and efficient than some of the conventional methods used in adaptive spectrum analysis and signal processing.",

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year = "1989",

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AB - A survey of various conjugate gradient (CG) algorithms is presented for the extreme eigen-probiems of a symmetric matrix. The CG algorithms are compared to a commonly used conventional method found in IMSL. It is concluded that the CG algorithms are more flexible and efficient than some of the conventional methods used in adaptive spectrum analysis and signal processing.

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A Survey of Conjugate Gradient Algorithms for Solution of Extreme Eigen-Problems of a Symmetric Matrix

Abstract

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