Application of Neural Network For Solving Linear Algebraic Equations


In this paper, we present an neural network approach to solve a set of linear algebraic equations. A Black-Box Neuro- Identifier network has been developed to optimize an convergence until getting the optimal solutions. Black- Box approach called also (input-output description) which is used when no information is available about the system except its input and output. The input-output description of a system gives a mathematical relationship between the input and output of the system. In developing this description, the knowledge of the internal structure of a system may be assumed to be unavailable; the only access to the system is by means of the input and output terminals. Our approach called Black Box Neural Network(BBNN) which provided an optimal solution and a faster way to solve the linear systems; and considered the best with large systems ( the number of equations and parameters very large) and conceded the first step to apply this approach with nonlinear algebraic equations which needs difficult computes and long time relatively.