TITLE:
A Class of Generalized Approximate Inverse Solvers for Unsymmetric Linear Systems of Irregular Structure Based on Adaptive Algorithmic Modelling for Solving Complex Computational Problems in Three Space Dimensions
AUTHORS:
Anastasia-Dimitra Lipitakis
KEYWORDS:
Adaptive Algorithms, Algorithmic Modelling, Approximate Inverse, Incomplete LU Factorization, Approximate Decomposition, Unsymmetric Linear Systems, Preconditioned Iterative Methods, Systems of Irregular Structure
JOURNAL NAME:
Applied Mathematics,
Vol.7 No.11,
July
12,
2016
ABSTRACT: A class of general inverse matrix
techniques based on adaptive algorithmic modelling methodologies is derived
yielding iterative methods for solving unsymmetric linear systems of irregular
structure arising in complex computational problems in three space dimensions.
The proposed class of approximate inverse is chosen as the basis to yield
systems on which classic and preconditioned iterative methods are explicitly
applied. Optimized versions of the proposed approximate inverse are presented
using special storage (k-sweep) techniques leading to economical forms of the
approximate inverses. Application of the adaptive algorithmic methodologies on
a characteristic nonlinear boundary value problem is discussed and numerical
results are given.