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中文摘要：
利用几何代数的多维统一性与运动表达的简明性,构建了面向多维向量场的辐散辐合结构特征的自适应匹配方法.利用rotor（旋转）结构的一致性表达,建立基于奇异值分解的原始模板与标准辐散模板间的最优rotor求解方法,进而实现了数据自适应的辐散辐合模板生成;基于rotor的旋转角度实现对向量场的几何结构的分类,构建了基于Clifford卷积的自适应模板的匹配算法.基于北美风场数据的算法验证结果显示,本文方法可以有效的解析出不同维度向量场的结构特征,并可实现基于结构特征的向量场分类.
英文摘要：
Taking advantage of the multidimensional unified and simplicity expression of movement characteristics of geometric algebra,an adaptive template matching method for convergence and divergence structure of multi-dimensional vector fields was proposed.The optimal rotor between the original vector field and the standard template is established based on SVD（Singular Value Decomposition）.The data adaptive divergence-convergence template generation method is then constructed based on the structure consistency of rotor rotation,and the classification of geometric structure of the vector field based on the rotor rotation angle is proposed.Finally,the adaptive template matching method is constructed based on the geometric convolution.These methods are verified with the wind field of North America.The results suggest that our method can effectively resolve the structural features of the vector field with different dimensions and can do structure-based classification of vector fields.
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