This paper presents a neural-network solver for the solution of the linear system of equations, where the coefficient matrix is a symmetric positive definite. The main idea of the method is that the linear system of equations is factored in the form of linear algebraic equations, and then the neural-network model is constructed by this algebraic equation. The Recursive Least-square (RLS) algorithm is used to train the weight vector of the neural network. The results reveal that the proposed method is ver...
