Applied Mathematics

Volume 6, Issue 8 (July 2015)

ISSN Print: 2152-7385   ISSN Online: 2152-7393

Formulation of a Preconditioned Algorithm for the Conjugate Gradient Squared Method in Accordance with Its Logical Structure

Author(s)
In this paper, we propose an improved preconditioned algorithm for the conjugate gradient squared method (improved PCGS) for the solution of linear equations. Further, the logical structures underlying the formation of this preconditioned algorithm are demonstrated via a number of theorems. This improved PCGS algorithm retains some mathematical properties that are associated with the CGS derivation from the bi-conjugate gradient method under a non-preconditioned system. A series of numerical comparisons with the conventional PCGS illustrate the enhanced effectiveness of our improved scheme with a variety of preconditioners. This logical structure underlying the formation of the improved PCGS brings a spillover effect from various bi-Lanczos-type algorithms with minimal residual operations, because these algorithms were constructed by adopting the idea behind the derivation of CGS. These bi-Lanczos-type algorithms are very important because they are often adopted to solve the systems of linear equations that arise from large-scale numerical simulations.

Share and Cite:

Itoh, S. and Sugihara, M. (2015) Formulation of a Preconditioned Algorithm for the Conjugate Gradient Squared Method in Accordance with Its Logical Structure. Applied Mathematics, 6, 1389-1406. doi: 10.4236/am.2015.68131.

Cited by

 [1] Changing over stopping criterion for stable solving nonsymmetric linear equations by preconditioned conjugate gradient squared method 2019 [2] Structure of the preconditioned system in various preconditioned conjugate gradient squared algorithms 2019 [3] Structure of the polynomials in preconditioned BiCG algorithms and the switching direction of preconditioned systems 2016 [4] Analysis of the structure of the Krylov subspace in various preconditioned CGS algorithms arXiv preprint arXiv:1603.00176, 2016 [5] The structure of the polynomials in preconditioned BiCG algorithms and the switching direction of preconditioned systems arXiv preprint arXiv:1603.00175, 2016 [6] The structure of the Krylov subspace in various preconditioned CGS algorithms arXiv, 2016

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