论文标题
高斯固定过程之间的最佳运输
Optimal Transport between Gaussian Stationary Processes
论文作者
论文摘要
我们考虑多元高斯固定随机过程之间的最佳运输问题。运输工作是过滤差异过程的差异。该技术说明的主要贡献是表明，相应的解决方案导致多元功率频谱密度之间的加权Hellinger距离。然后，在基于此距离的间接测量情况下，我们提出了一种光谱估计方法。
We consider the optimal transport problem between multivariate Gaussian stationary stochastic processes. The transportation effort is the variance of the filtered discrepancy process. The main contribution of this technical note is to show that the corresponding solution leads to a weighted Hellinger distance between multivariate power spectral densities. Then, we propose a spectral estimation approach in the case of indirect measurements which is based on this distance.
