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L. Duane Pyle

dblp:38/2336 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1964
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Mathematical optimization · 50% Algorithms and data structures · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithms and data structures › numerical linear algebra
generalized inverse
0.011964
Generalized Inverse Computations Using the Gradient Projection Method · J. ACM 1964
Mathematical optimization
linear programming
0.011964
Generalized Inverse Computations Using the Gradient Projection Method · J. ACM 1964

Methods — techniques the papers use, named apart from their topics

gram-schmidt orthogonalization · 0.0gradient projection · 0.0conjugate directions · 0.0
YearPublicationVenuePosition
1964 Generalized Inverse Computations Using the Gradient Projection Method
abstract
A number of methods have been proposed for computing the (Moore-Penrose-Bjerhammar) generalized inverse A + of an arbitrary m X n complex matrix A of rank r < m _~ n.Boot, Ben~Israel and Wersan have recently published methods which require the formation either of AA* or BB*, where B is an r X n submatrix of A having rank r.In this paper a procedure for computing A + is given which consists of a variant of the gradient projection method.The procedure, which is equivalent to a Hestenes conjugate directions method in the special case r = m, may be applied to any complex matrix.The basic procedure requires the application of the Gram-Schmidt orthogonalization process, first to the column vectors of A*, then, if A is not of full row rank, to the column vectors of A. A computer program (FoRTRXN IV for the IBM 7090) using the method has been tested and used in connection with the generalized inverse-eigenvector method for solving linear programruing problems.
L. Duane Pyle
J. ACM1