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Functional and Structural Features of Recurrent Neural Networks with Controlled Elements

  • Vasiliy OsipovEmail author
  • Viktor Nikiforov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11554)

Abstract

The features of recurrent neural networks with controlled elements are considered. The functions of these networks for controlled associative processing of signals are refined. A number of the space-time structures of such networks are analyzed. Among them, the neural networks with one-, two-, and three-level structures of layers are investigated. The results of studies on the stability of the associative processing of distorted signals by these networks are reflected. Based on the simulation results, recommendations are formulated to expand the possibilities of associative signal processing in recurrent neural networks with controlled elements.

Keywords

Recurrent neural network Logical structure Associative signal processing Control 

Notes

Acknowledgement

This research is partially supported by the RFBR foundation grant No 16-29-09482.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.St. Petersburg Institute for Informatics and Automation of Russian Academy of SciencesSt. PetersburgRussia

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