A classic algorithm for solving linear systems, dubbed Gaussian elimination in modern times, was first published by Chinese mathematicians 2,000 years ago.

An algorithm for the decomposition of a mixture of Gaussian components is given, partially in Algol-60 language, and experiences with its use on a digital computer are described. The algorithm ...

When Gaussian errors are inappropriate in a multivariate linear regression setting, it is often assumed that the errors are iid from a distribution that is a scale mixture of multivariate normals.

Matrix inversion using GJ-elimination improves the frequency when compared with QR decomposition algorithm. The design is targeted on XC5VLX50T Xilinx FPGA.