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arXiv 1710.06362math.NAcs.NA
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利用同伦持续方法求解参数化系统的自适应策略

Adaptive strategies for solving parameterized systems using homotopy continuation

University of Notre Dame(圣母大学)

Jonathan D. Hauenstein, Margaret H. Regan

AI总结:

本文研究了同伦持续法在求解参数化多项式方程组中的应用,探讨了自适应选择仿射坐标补丁、选择良约束子系统及识别非实解路径的方法,通过计算机视觉中的两个问题验证了这些策略的有效性。

摘要:

本文研究了同伦持续法在求解参数化系统中的三个方面。首先,针对齐次参数化系统,探讨了在自适应选择的仿射坐标补丁上进行计算的选项。其次,针对过定系统,探讨了自适应选择良约束子系统以恢复数值稳定性的选项。最后,由于通常只关心应用中参数化问题的实解,探讨了一种启发式方法来识别似乎结束于非实解的解路径并截断它们。我们通过计算机视觉中的两个问题展示了这三个方面的应用。

英文摘要:

Three aspects of applying homotopy continuation, which is commonly used to solve parameterized systems of polynomial equations, are investigated. First, for parameterized systems which are homogeneous, we investigate options for performing computations on an adaptively chosen affine coordinate patch. Second, for parameterized systems which are overdetermined, we investigate options for adaptively selecting a well-constrained subsystem to restore numerical stability. Finally, since one is typically interested in only computing real solutions for parameterized problems which arise from applications, we investigate a scheme for heuristically identifying solution paths which appear to be ending at nonreal solutions and truncating them. We demonstrate these three aspects on two problems arising in computer vision.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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