Problems Encountered during Implementation of the Backpropagation

摘要

Backpropagation is one of the most popular neural networks and is widely applied in various problems. Despite its wide application, there are some major problems encountered during implementation of Backpropagation such as the appropriate decision for the network topology, learning parameter, initial weights, and data sets for training. Although the network performance is sensitive to these elements which should be determined prior to the implementation of Backpropagation, there is no efficient rule for the proper choice of these to achieve the best performance.