Historical Consistent Complex Valued Recurrent Neural Network

نویسندگان

  • Hans-Georg Zimmermann
  • Alexey Minin
  • Victoria Kusherbaeva
چکیده

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.

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تاریخ انتشار 2011