This important study shows a surprising scale-invariance of the covariance spectrum of large-scale recordings in the zebrafish brain in vivo. A convincing analysis demonstrates that a Euclidean random ...

We use the covariance matrix to model the feature heterogeneity and redundancy and propose Correlation-Aware Covariance Weighting (CACW) to adjust them. CACW captures these correlations through the ...

In this study we give short overview of polarimetric SAR image visualization with colors. By studying the color models and polarization visualization models we propose basic principles which should be ...

Is this real life? Is this just fantasy? A growing number of scientists are suggesting that the idea that we are all living in a simulation may not be completely far-fetched. Simulation theory is ...

This article presents a from-scratch C# implementation of the first technique: compute eigenvalues and eigenvectors from the covariance matrix. If you're not familiar with PCA, most of the terminology ...

This paper proposes a novel shrinkage estimator for high-dimensional covariance matrices by extending the Oracle Approximating Shrinkage (OAS) of Chen et al. (2009) to target the diagonal elements of ...

Building upon our previous implementation (Baker and Porollo, 2016), the covariance matrices were compared with those processed using graphical LASSO to obtain estimated covariance matrix and its ...

The covariance matrix for the filtered 10-channel EEG was estimated. All previous 1-s EEG covariance matrices that belonged to the feedback period within the current run were saved, the number of ...