Abstract. For an n n tridiagonal matrix we exploit the structure of its QR factorization to devise two new algorithms for computing the 1-norm condition number in O(n) operations. The algorithms avoid under ow and over ow, and are simpler than existing algorithms since tests are not required for degenerate cases. An error analysis of the rst algorithm is given, while the second algorithm is shown to be competitive in speed with existing algorithms. We then turn our attention to an n n diagonal-plus-semiseparable matrix, A, for which several algorithms have recently been developed to solve Ax = b in O(n) operations. We again exploit the QR factorization of the matrix to present an algorithm that computes the 1-norm condition number in O(n)...
In this paper we present a linear time algorithm for checking whether a tridiagonal matrix will beco...
Numerical algorithms are considered for three distinct areas of numerical linear algebra: hyperbolic...
The standard procedure to compute the singular value decomposition of a dense matrix, first reduces i...
Abstract. For an n n tridiagonal matrix we exploit the structure of its QR factorization to devise ...
For an $n \times n$ tridiagonal matrix we exploit the structure of its QR factorization to devis...
Abstract. We present one more algorithm to compute the condition number (for inversion) of an n × n ...
Let A be a tridiagonal matrix of order n. We show that it is possible to compute and hence condo (A)...
Several properties of matrix norms and condition numbers are described. The sharpness of the norm bo...
The QR algorithm computes a Schur decomposition of a matrix. It is certainly one of the most importa...
The QR algorithm is one of the classical methods to compute the eigendecomposition of a matrix. If i...
The QR algorithm is one of the classical methods to compute the eigendecomposition of a matrix. If ...
AbstractIn this paper we discuss the structure of the factors of a QR- and a URV-factorization of a ...
In this paper we present a linear time algorithm for checking whether a tridiagonal matrix will beco...
The standard procedure to compute the singular value decomposition of a dense matrix, first reduces i...
We show how both the tridiagonal and bidiagonal QR algorithms can be restructured so that they be- ...
In this paper we present a linear time algorithm for checking whether a tridiagonal matrix will beco...
Numerical algorithms are considered for three distinct areas of numerical linear algebra: hyperbolic...
The standard procedure to compute the singular value decomposition of a dense matrix, first reduces i...
Abstract. For an n n tridiagonal matrix we exploit the structure of its QR factorization to devise ...
For an $n \times n$ tridiagonal matrix we exploit the structure of its QR factorization to devis...
Abstract. We present one more algorithm to compute the condition number (for inversion) of an n × n ...
Let A be a tridiagonal matrix of order n. We show that it is possible to compute and hence condo (A)...
Several properties of matrix norms and condition numbers are described. The sharpness of the norm bo...
The QR algorithm computes a Schur decomposition of a matrix. It is certainly one of the most importa...
The QR algorithm is one of the classical methods to compute the eigendecomposition of a matrix. If i...
The QR algorithm is one of the classical methods to compute the eigendecomposition of a matrix. If ...
AbstractIn this paper we discuss the structure of the factors of a QR- and a URV-factorization of a ...
In this paper we present a linear time algorithm for checking whether a tridiagonal matrix will beco...
The standard procedure to compute the singular value decomposition of a dense matrix, first reduces i...
We show how both the tridiagonal and bidiagonal QR algorithms can be restructured so that they be- ...
In this paper we present a linear time algorithm for checking whether a tridiagonal matrix will beco...
Numerical algorithms are considered for three distinct areas of numerical linear algebra: hyperbolic...
The standard procedure to compute the singular value decomposition of a dense matrix, first reduces i...