A New Spectral Conjugate Gradient Method and Its Global Convergence
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@Article{JICS-8-075,
author = {Min SUN and Jing LIU},
title = {A New Spectral Conjugate Gradient Method and Its Global Convergence},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {8},
number = {1},
pages = {075--080},
abstract = {Combining the advantage of spectral-gradient method, a spectral conjugate gradient method for
the global optimization is presented. This method has the property that the generated search direction is
sufficiently descent without utilizing the line search. The proof of the convergence of the proposed method is
given. Numerical experiments show that the method is efficient and feasible.
},
issn = {1746-7659},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22630.html}
}
TY - JOUR
T1 - A New Spectral Conjugate Gradient Method and Its Global Convergence
AU - Min SUN and Jing LIU
JO - Journal of Information and Computing Science
VL - 1
SP - 075
EP - 080
PY - 2024
DA - 2024/01
SN - 8
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22630.html
KW - spectral conjugate gradient method
KW - sufficient descent
KW - global convergence
AB - Combining the advantage of spectral-gradient method, a spectral conjugate gradient method for
the global optimization is presented. This method has the property that the generated search direction is
sufficiently descent without utilizing the line search. The proof of the convergence of the proposed method is
given. Numerical experiments show that the method is efficient and feasible.
Min SUN and Jing LIU. (2024). A New Spectral Conjugate Gradient Method and Its Global Convergence.
Journal of Information and Computing Science. 8 (1).
075-080.
doi:
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