基于半参数模型的GPS系统误差处理的关键之一是选择合适的正则化矩阵。
One of the crucial steps is choosing an appropriate regularizer in processing GPS systematic errors based on the semi-parametric model.
其基本思想是利用验前模型信息确定正则化矩阵,利用验后观测信息确定自适应因子。
The regularization matrix will be chosen by prior information of the model parameters and the adaptive factor, however, will be determined by posterior information.
基于TIK - HONOV正则化原理,选择了一种具有物理意义的正则化矩阵,以减弱法矩阵的病态性。
Based on TIKHONOV regularization theorem, a new regularizer, which has explicitly physical meaning, is chosen to mitigate the ill-condition of the normal matrix.
提出一种新的非线性结构张量计算方法,扩展了基于迹的PDE正则化方法,使其适用于矩阵值数据场;
A new nonlinear structure tensor calculation method is presented. We extend the trace-based PDE regularization method to matrix-valued data fields.
提出一种新的非线性结构张量计算方法,扩展了基于迹的PDE正则化方法,使其适用于矩阵值数据场;
A new nonlinear structure tensor calculation method is presented. We extend the trace-based PDE regularization method to matrix-valued data fields.
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