✦ LIBER ✦

Indefinite QR Factorization

✍ Scribed by Sanja Singer

Book ID: 106372938
Publisher: Springer Netherlands
Year: 2006
Tongue: English
Weight: 596 KB
Volume: 46
Category: Article
ISSN: 0006-3835
DOI: 10.1007/s10543-006-0044-5

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Rounding-error and perturbation bounds f

Rounding-error and perturbation bounds for the indefinite QR factorization

✍ Sanja Singer; Saša Singer 📂 Article 📅 2000 🏛 Elsevier Science 🌐 English ⚖ 139 KB

Indefinite QR factorization is a generalization of the well-known QR factorization, where Q is a unitary matrix with respect to the given indefinite inner product matrix J. This factorization can be used for accurate computation of eigenvalues of the Hermitian matrix A = G \* J G, where G and J are

Solving the Indefinite Least Squares Pro

Solving the Indefinite Least Squares Problem by Hyperbolic QR Factorization

✍ Bojanczyk, Adam; Higham, Nicholas J.; Patel, Harikrishna 📂 Article 📅 2003 🏛 Society for Industrial and Applied Mathematics 🌐 English ⚖ 196 KB

A backward stable hyperbolic QR factoriz

A backward stable hyperbolic QR factorization method for solving indefinite least squares problem

✍ Hong-guo Xu 📂 Article 📅 2004 🏛 Chinese Electronic Periodical Services 🌐 English ⚖ 373 KB

On QR factorization updatings

✍ L. F. Escudero 📂 Article 📅 1984 🏛 Springer-Verlag ⚖ 476 KB

QR factorization of confluent Vandermond

QR factorization of confluent Vandermonde matrices

✍ Demeure, C.J. 📂 Article 📅 1990 🏛 IEEE ⚖ 362 KB

Adaptive blocking in the QR factorizatio

Adaptive blocking in the QR factorization

✍ Christian H. Bischof 📂 Article 📅 1989 🏛 Springer US 🌐 English ⚖ 888 KB

On most high-performance architectures, data movement is slow compared to floating point (in particular, vector) performance. On these architectures block algorithms have been successful for matrix computations. By considering a matrix as a collection of submatrices (the so-called blocks), one natur