Visual Studio Magazine

Computing the Determinant of a Matrix Using Gaussian Elimination to Row Echelon Form with C#

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 ...
TechRepublic

Implementation of Complex Matrix Inversion Using Gauss-Jordan Elimination Method in Verilog

For high data rate wireless communications they use Orthogonal Frequency Division Multiplexing (OFDM) due to its high spectral efficiency and low computational complexity. It gives the architecture of ...
JSTOR Daily

GRAPH ESTIMATION FOR MATRIX-VARIATE GAUSSIAN DATA

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 ...
JSTOR Daily

GENERALIZED SPARSE PRECISION MATRIX SELECTION FOR FITTING MULTIVARIATE GAUSSIAN RANDOM FIELDS TO LARGE DATA SETS

We present a new method for estimating multivariate, second-order stationary Gaussian Random Field (GRF) models based on the Sparse Precision matrix Selection (SPS) algorithm, proposed by Davanloo ...