About: Tridiagonal matrix algorithm is a research topic. Over the lifetime, 1070 publications have been published within this topic receiving 21084 citations.
TL;DR: The proposed bounds reveal the sensitivity of the eigenvalues with respect to perturbations of different blocks and improve some existing ones for generalized saddle point matrices and Hermitian block tridiagonal matrices.
TL;DR: In this paper, the spectral properties of a class of tridiagonal matrices are investigated, and the reconstruction of matrices of this special class from given spectral data is also studied.
TL;DR: In this paper, a cross product function of the elements in the tridiagonal matrix is obtained by using the right-angled triangle property among the coefficients. But the lower triangle of the inverse of a general tridimensional matrix can be computed in a non-block case.
Abstract: In this study a further relationship is extended to the elements in the lower triangle of the inverse of a general tridiagonal matrix for a non‐block case. Once the upper triangle of the inverse is determined based on Huang and McColl's analytical inversion formula, the corresponding lower triangle can be calculated efficiently using two proposed theorems. Each element in the lower triangle is decomposed into two parts: one is the coefficient; the other the counterpart element in the upper triangle. The coefficient is a cross product function of the elements in the tridiagonal matrix and can be easily obtained by using the right‐angled triangle property among the coefficients. This results in a faster computation of the lower triangle of the inverse of a general tridiagonal matrix. Several examples are given to demonstrate the superiority of two theorems developed by the author to Huang and McColl's algorithm. It is shown that the algorithm based on the right‐angled triangle property outperforms ...