一般非线性方程的非精确梯度BFGS方法

IF 0.4 4区 数学 Q4 MATHEMATICS, APPLIED Pacific Journal of Optimization Pub Date : 2023-01-01 DOI:10.61208/pjo-2023-027
ZHOU Weijun, ZHANG Li
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引用次数: 0

摘要

介绍了一种全局超线性收敛的BFGS方法,用于求解一般非线性方程,无需计算精确梯度。与现有的基于高斯-牛顿的BFGS型方法相比,该方法不需要底层函数的对称性等条件。此外,它可以适当调整以解决非线性最小二乘问题,并仍然保证全局收敛。数值结果表明了该方法的有效性。
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A BFGS method using inexact gradient for general nonlinear equations
A globally and superlinearly convergent BFGS methods is introduced to solve general nonlinear equations without computing exact gradient. Compared with existing Gauss-Newton-based BFGS type methods, the proposed method does not require conditions such as sysmmetry on the underlying function. Moreover, it can be suitably adjusted to solve nonlinear least squares problems and still guarantee global convergence. Some numerical results are reported are reported to show its efficiency.
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来源期刊
Pacific Journal of Optimization
Pacific Journal of Optimization OPERATIONS RESEARCH & MANAGEMENT SCIENCE-MATHEMATICS, APPLIED
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审稿时长
3 months
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