ARTIFICIAL NEURAL NETWORKS AND ITERATIVE LINEAR ALGEBRA METHODS
Konstantinos G. Margaritis, Miltiades Adamopoulos, Konstantinos Goulianas, David John Evans · International Journal of Parallel Emergent and Distributed Systems · 1994
This paper describes the usage of feed-forward artificial neural networks, for the implementation of a variety of iterative methods of numerical linear algebra for solving linear systems of equations. Extensions to matrix based iterative procedures are also presented and the application of those iterative methods in neural network training algorithms is discussed. Finally, some experimented results are presented, comparing the various methods discussed.