Solving linear simultaneous equations by constraining learning neural networks
This paper proposes using constrained learning algorithm (CLA) to solve linear equations, where the corresponding conrtraint relations for this problem is just the linear equations. As a result. the CLA can be effectively and appropriately applied It was found in experiments that the convergent speedfor this CLA is much faster than the recursive least square back propagation (RLS-BP) algorithm. Finally, related experimental results are presented.