An Accelerating Learning Algorithm for Block-Diagonal Recurrent Neural Networks
Paris Mastorocostas, Dimitrios Varsamis, C. Mastorocostas, Ioannis T. Rekanos · 2006
An efficient training method for block-diagonal recurrent neural networks is proposed. The method modifies the RPROP algorithm, originally developed for static models, in order to be applied to dynamic systems. A comparative analysis with a series of algorithms and recurrent models is given, indicating the effectiveness of the proposed learning approach