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Iterative methods for weighted least-squares

Conference ·
OSTI ID:440701
;  [1]
  1. Cornell Univ., Ithaca, NY (United States)
A weighted least-squares problem with a very ill-conditioned weight matrix arises in many applications. Because of round-off errors, the standard conjugate gradient method for solving this system does not give the correct answer even after n iterations. In this paper we propose an iterative algorithm based on a new type of reorthogonalization that converges to the solution.
Research Organization:
Front Range Scientific Computations, Inc., Lakewood, CO (United States)
OSTI ID:
440701
Report Number(s):
CONF-9604167--Vol.2; ON: DE96015307
Country of Publication:
United States
Language:
English

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