Rprop was invented in 1992 as part of my master thesis on supervised learning algorithms for neural networks (supervised by Prof. Dr. Heinrich Braun). It introduces a novel type of adaptive gradient descent technique, where the update step is only based on the sign of the gradient and its temporal evolution, not its size. This leads to a very fast and very robust supervised learning algorithm for batch learning.

Video Visualization Back Propagation: RProp and iRProp+