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GLOBAL WEAK SHARP MINIMA AND COMPLETENESS OF METRIC SPACE
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作者 黄辉 《Acta Mathematica Scientia》 SCIE CSCD 2005年第2期359-366,共8页
A sufficient condition on the existence of a global weak sharp minima for general function in metric space is established. A characterization for convex function to have global weak sharp minima is also presented, whi... A sufficient condition on the existence of a global weak sharp minima for general function in metric space is established. A characterization for convex function to have global weak sharp minima is also presented, which generalized Burke and Ferris' result to infinite dimensional space. A characterization of the completeness of a metric space is given by the existence of global weak sharp minima. 展开更多
关键词 global weak sharp minima COMPLETENESS convex function
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A Numerical Method for Solving Ill-Conditioned Equation Systems Arising from Radial Basis Functions
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作者 Edward J. Kansa 《American Journal of Computational Mathematics》 2023年第2期356-370,共15页
Continuously differentiable radial basis functions (C<sup>∞</sup>-RBFs), while being theoretically exponentially convergent are considered impractical computationally because the coefficient matrices are ... Continuously differentiable radial basis functions (C<sup>∞</sup>-RBFs), while being theoretically exponentially convergent are considered impractical computationally because the coefficient matrices are full and can become very ill- conditioned. Similarly, the Hilbert and Vandermonde have full matrices and become ill-conditioned. The difference between a coefficient matrix generated by C<sup>∞</sup>-RBFs for partial differential or integral equations and Hilbert and Vandermonde systems is that C<sup>∞</sup>-RBFs are very sensitive to small changes in the adjustable parameters. These parameters affect the condition number and solution accuracy. The error terrain has many local and global maxima and minima. To find stable and accurate numerical solutions for full linear equation systems, this study proposes a hybrid combination of block Gaussian elimination (BGE) combined with arbitrary precision arithmetic (APA) to minimize the accumulation of rounding errors. In the future, this algorithm can execute faster using preconditioners and implemented on massively parallel computers. 展开更多
关键词 Continuously Differentiable Radial Basis Functions global Maxima and Minima Solutions of Ill-Conditioned Linear Equations Block Gaussian Elimination Arbitrary Precision Arithmetic
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