Complexity analysis indicates that when applied to compute the Moore–Penrose inverse, our method is more efficient than the existing Gauss–Jordan elimination methods in the literature for a large class of problems. Finally, numerical experiments show our method for Moore–Penrose inverse has good ...
The Gauss-Jordan elimination is not quite stable numerically. In order to get better and more stable schemes, a common practice is to use pivoting. Basically, pivoting is a scaling procedure by dividing all the elements in a row by the element with the largest magnitude or norm. If necessary...
We formulate a number of theorems that give estimates for the local Şll-in of such matrices on some stages of Gaussian elimination. As the result, we derive that only the suggested modiŞcation of Gauss method appeared to be eŞective and economical one from the standpoint of CPU time ...
The analysis of computational complexity indicates that our algorithm is more efficient than the existing Gauss-Jordan elimination algorithms for \\(A_{R(G),N(G)}^{(2)}\\) in the literature for a large class of problems. Especially for the case when G is a Hermitian matrix, our ...