In this paper, by exploiting the special structure of the least squares problem and working on the problem directly, a numerically stable QR decomposition based algorithm is presented for the problem.

If the source matrix is a covariance matrix, then using Cholesky decomposition is efficient. The implementation of QR-Householder matrix inverse presented in this article emphasizes simplicity and ...

Four examples include 1.) LUP decomposition algorithm (Crout version), 2.) QR decomposition algorithm (Householder version), 3.) SVD decomposition algorithm (Jacobi version), 4.) Cholesky ...

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