One of the fundamental operations in machine learning is computing the inverse of a square matrix. But not all matrices have an inverse. The most common way to check if a matrix has an inverse or not ...

It gives the architecture of an optimized complex matrix inversion using Gauss-Jordan (GJ) elimination in Verilog with single precision floating-point representation.

Matrix-variate Gaussian graphical models (GGM) have been widely used for modeling matrix-variate data. Since the support of sparse precision matrix represents the conditional independence graph among ...

It is a classical result of Ginibre that the normalized bulk k-point correlation functions of a complex n × n Gaussian matrix with independent entries of mean zero and unit variance are asymptotically ...