Improved Inverse-Based Solution Model of Zhang Neuronet for Time-Dependent Cholesky Factorization

Time-dependent Cholesky factorization is investigated and solved further in this paper. An improved solution model via Zhang neuronet (ZN) is proposed with constraint conditions considered. At first, we combine the objective equations and constraint conditions into new equations. The final coefficient matrix of the new equations (as an equation group) is invertible. Then, the new equations are solved by using inverse. The improved ZN solution model accurately solves the problem, and it exponentially converges to the theoretical solution. Numerical experiments and results substantiate the efficacy and the superiority of the improved ZN solution model.