What Other Iterative Methods Can Be Used If A is Not Positive Definite?

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SUMMARY

The discussion focuses on solving the linear system Ax=B when matrix A is not positive definite. Participants recommend alternative iterative methods such as the Generalized Minimal Residual (GMRES) method and the Bi-Conjugate Gradient (BiCG) method. These methods are suitable for non-symmetric or indefinite matrices, providing effective solutions where the Conjugate Gradient method fails. The importance of selecting the appropriate preconditioner is also emphasized to enhance convergence rates.

PREREQUISITES
  • Understanding of linear algebra concepts, particularly matrix properties.
  • Familiarity with iterative methods for solving linear systems.
  • Knowledge of preconditioning techniques in numerical analysis.
  • Experience with computational tools such as MATLAB or Python libraries for numerical computations.
NEXT STEPS
  • Research the Generalized Minimal Residual (GMRES) method and its applications.
  • Explore the Bi-Conjugate Gradient (BiCG) method and its advantages for non-symmetric matrices.
  • Study preconditioning techniques to improve the performance of iterative methods.
  • Experiment with MATLAB or Python implementations of these iterative methods on non-positive definite matrices.
USEFUL FOR

Mathematicians, numerical analysts, and engineers dealing with linear systems, particularly those working with non-positive definite matrices and seeking efficient iterative solutions.

Milentije
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I am dealing with a problem,which can be formulated Ax=B,in the first place I wanted to solve it with conjugate gradient method.BUt A is not positive definite.Which are the other iterative options in this case?
 
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