Recurrent Trainable Neural Networks for Complex Systems Identification: A Hybrid System Approach

نویسندگان

  • Juan Eduardo Velázquez-Velázquez
  • Rosalba Galván-Guerra
  • Ieroham Baruch
  • Silvestre Garcia-Sanchez
چکیده

This paper is devoted to the development of an Identification Framework for unknown Complex Systems. The proposal is based on Recurrent Trainable Neural Networks following a Hybrid System approach. The complex system is identified by using hybrid input-output data defined by a given set of switching hypersurfaces. The effectiveness of the proposed approach is shown using a commutable pendulum with chaotic behavior.

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عنوان ژورنال:
  • Research in Computing Science

دوره 118  شماره 

صفحات  -

تاریخ انتشار 2016