2021/08/16 by Yu.Yu. Yurchenko, Yurchenko, Yurii
Mathematics · Computer Science · #Tensor decomposition and applications #Computational Physics and Python Applications #Gaussian Processes and Bayesian Inference
paper · pdf · doi:10.48550/arxiv.2108.07245
In this article, we define the matricization of a tensor and we present some properties of the matricization. After that, we define the determinant of a tensor and we present some properties of the determinant. We define the covariance tensor and we present some properties of the covariance tensor. In a similar way, we define the correlation tensor. We define the tensor normal distribution. In a similar way, we define the tensor elliptical distributions. We prove the equivalence of the tensor elliptical distribution representations.