A new convergence case for FGDIP

In this article we introduce a new convergence case for an integral partition method called Feedback Guided Dynamic Integral Partition (FGDIP). The method generates iteratively a sequence of integral bounds by re-balancing the previous integral partition to achieve a better one. The convergence of the bounds is proven when the initial function does not have large variations. Experimental results show that the proposed method FGDIP achieves better performance than the classical Newton's method.