A recursive root moment method for finding roots of polynomials based on neural constrained learning method

This paper proposes using the recursive root moment method (RRMM) based on feedforward neural networks (FNN) trained by a constrained learning algorithm (CLA) to find the roots of polynomials, which is of lower computational complexity than the root moment method (RMM) and the method using the relations between the roots and the coefficients (RRC) of polynomials. As a result, the RRMM has faster training speed and higher accuracy than the latter two methods. The experimental results verify our claims.