Name
Abstract | ||
|---|---|---|
This paper describes how, given the Jacobi matrixJ for the measure dσ(t), it is possible to produce the Jacobi matrix Ĵ for the measurer(t)dσ(t) wherer(t) is a quotient of polynomials. The method uses a new factoring algorithm to generate the Jacobi matrices associated with the partial fraction decomposition ofr(t) and then applies a previously developed summing technique to merge these Jacobi matrices. The factoring method performs best just where Gautschi's minimal solution method for this problem is weakest and vice versa. This suggests a hybrid strategy which is believed to be the most powerful yet for solving this problem. The method is demonstrated on a simple example and some numerical tests illustrate its performance characteristics. |
Year | DOI | Venue |
|---|---|---|
1994 | 10.1007/BF02142672 | Numerical Algorithms |
Keywords | Field | DocType |
Orthogonal polynomials,Jacobi matrices,rational factors modifying measures,Gauss quadratures | Mathematical optimization,Jacobi rotation,Jacobi method,Orthogonal polynomials,Mathematical analysis,Jacobi operator,Matrix (mathematics),Jacobi eigenvalue algorithm,Jacobi polynomials,Partial fraction decomposition,Mathematics | Journal |
Volume | Issue | Citations |
6 | 2 | 5 |
PageRank | References | Authors |
1.41 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| S. Elhay | 1 | 28 | 18.57 |
| Jaroslav Kautsky | 2 | 108 | 20.75 |