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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국산업응용수학회 JOURNAL OF THE KOREAN SOCIETY FOR INDUSTRIAL AND APPLIED MATHEMATICS Journal of the Korean Society for Industrial and Applied Mathematics Vol.9 No.1
- 발행연도
- 2005.6
- 수록면
- 55 - 61 (7page)
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초록· 키워드
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A Conjugate Gradient algorithm for unconstrained minimization is pro-posed which is invariant to a nonlinear scaling of a strictly convex quadratic function and which generates mutually conjugate directions for extended quadratic functions. It is derived for inexact line searches and for general functions. It compares favourably in numerical tests (over eight test functions and dimensionality up to 1000) with the Dixon (1975 ) algorithm on which this new algorithm is based .
목차
ABSTRACT
1. INTRODUCTON
2. DERIVATION OF ρi
3. ALGORITHM EDIX
4. COMPUTATIONAL RESULTS AND CONCLUSION
REFERENCES
Appendix
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UCI(KEPA) : I410-ECN-0101-2009-410-014676832