Conditions for the bivariate characteristic polynomial of a matrix to be very strict Hurwitz are presented. These conditions are based on the necessary and sufficient conditions for the existence of ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Cayley-Hamilton technique. Compared to other matrix inverse algorithms, ...

In this article, we investigate the leader–follower consensus of multiagent systems over finite fields, which model agents with limited capacities for storing, processing, and transmitting the ...

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 ...

1: Why the diagonal elements of covariance matrix have negative values? 2: Is there any way to avoid the situation where the diagonal elements in the covariance matrix is negative? 3: If the diagonal ...

numpy.polynomial.polynomial.polyfit does not return covariance matrix. The older numpy.polyfit does, but using numpy.polynomial.polynomial.polyfit is prefered as it is part of the new numpy.polynomial ...

Mueller matrix images of the structures show close resemblance to numerical simulations and significant influence of sub-wavelength features to off-diagonal matrix elements.

Figure 1. The overall workflow of the non-negative matrix factorization network analysis (NMFNA) for identifying modules and characteristic genes by integrating methylation (ME) and copy number ...