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Computing with sparse matrices

✍ Scribed by T. S. Chow; J. S. Kowalik

Publisher: John Wiley and Sons
Year: 1973
Tongue: English
Weight: 866 KB
Volume: 7
Category: Article
ISSN: 0029-5981
DOI: 10.1002/nme.1620070210

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📜 SIMILAR VOLUMES

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This paper is a survey of methods currently available for processing sparse matrices in a digital computer; specifically in the solution of linear algebraic equations and the eigenproblem.

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Starting from recent formulas for calculating the permanents of some sparse circulant matrices, we obtain more general formulas expressing the permanents of a wider class of matrices as a linear combination of appropriate determinants.

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The minimum number of nonzero entries in an n by n orthogonal matrix which has a column of nonzeros is known to be In this note the sparsity of orthogonal matrices which have both a column and a row of nonzeros is studied. For each integer n 2 we construct an n by n orthogonal matrix which has both

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✍ Charles R. Johnson; Michael Lundquist 📂 Article 📅 1998 🏛 Elsevier Science 🌐 English ⚖ 274 KB

We demonstrate that subject to certain regularity conditions any invertible matrix whose inverse is subordinate to a chordal graph G may be inverted via a simple formula involving only the inverses of its principal submatrices corresponding to the maximal cliques and minimal vertex separators of the