Convergence analysis of the Quickprop method

A mathematical framework for the convergence analysis of the well known Quickprop method is described. The convergence of this method is analyzed. Furthermore, we present modifications of the algorithm that exhibit improved convergence speed and stability and at the same time, alleviate the use of heuristic learning parameters. Simulations are conducted to compare and evaluate the performance of a proposed modified Quickprop algorithm with various popular training algorithms. The results of the experiments indicate that the increased convergence rates, achieved by the proposed algorithm, affect by no means its generalization capability and stability