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IMPROVING COMPARISON RESULTS ON PRECONDITIONED GENERALIZED ACCELERATED OVERRELAXATION METHODS
IMPROVING COMPARISON RESULTS ON PRECONDITIONED GENERALIZED ACCELERATED OVERRELAXATION METHODS
Journal of applied mathematics & informatics. 2015. Jan, 33(1_2): 193-201
  • Received : March 19, 2014
  • Published : January 30, 2015
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Wang Guangbin
Sun Deyu

Abstract
In this paper, we present preconditioned generalized accelerated overrelaxation (GAOR) methods for solving weighted linear least square problems. We compare the spectral radii of the iteration matrices of the preconditioned and the original methods. The comparison results show that the preconditioned GAOR methods converge faster than the GAOR method whenever the GAOR method is convergent. Finally, we give a numerical example to confirm our theoretical results.
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