Historical consistent complex valued recurrent neural network

Authors:
Hans-Georg Zimmermann;Alexey Minin;Victoria Kusherbaeva
Affiliations:
Siemens AG, Corporate Technology, Muenchen, Germany;Technische Universitat Munchen, Institut fur Informatik, Muenchen, Germany and Siemens LLC, Corporate Technology, St. Petersburg, Russia;Siemens LLC, Corporate Technology, St. Petersburg, Russia
Venue:
ICANN'11 Proceedings of the 21th international conference on Artificial neural networks - Volume Part I
Year:
2011

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Abstract

Recurrent Neural Networks are in the scope of the machine learning community for many years. In the current paper we discuss the Historical Consistent Recurrent Neural Network and its extension to the complex valued case. We give some insights into complex valued back propagation and its application to the complex valued recurrent neural network training. Finally we present the results for the the Lorenz system modeling. In the end we discuss the advantages of the proposed algorithm and give the outlook.