11. Performing PCA directly on the covariance matrix of the images is often computationally infeasible. 12. Exploiting the Hermitian symmetry of the covariance matrix R _ v, we can write 13. Consequently, the covariance matrix of the reduced VAR 14. Pairwise dependencies between the variables in the distribution are represented by a covariance matrix . 15. This ensures that the covariance matrix will accurately represent the distribution of the errors. 16. LMC, process convolution ) used to compute the multi-output covariance matrix . 17. Consequently, the virtue of a robust covariance matrix in this setting is unclear . 18. A simple version of a shrinkage estimator of the covariance matrix is constructed as follows. 19. However, maintaining the covariance matrix is not feasible computationally for high-dimensional systems. 20. Conversely, every positive semi-definite matrix is the covariance matrix of some multivariate distribution.
