A Direct Decomposition Method for the Solution of Sparse Linear Least Squares Problems
Abstract
Given a sparse nonsquare system of linear equations Mx = b where M(T) M is either dense or full, we present a direct method that generates a least squares solution of the original system by solving a smaller least squares problem. The method accomplishes this decomposition by applying orthogonal transformations to a restructured form of the original system of equations Mx = b. The algorithms derived from the decomposition result are well suited for both sequential and parallel architecture machines. In a specific Navy signal processing application, the presented algorithm computed on a Sun SPARC 10 workstation a least squares solution of a rank deficient system comprising 703 equations and 592 variables in a number of floating point computations tenfold smaller than a method that does not exploit the sparsity structure of M. Sparse linear least squares
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 1994
- Accession Number
- ADA284060
Entities
People
- A. K. Kevorkian
Organizations
- Naval Command, Control and Ocean Surveillance Center