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Formal Aspects of Streaming Recurrent Neural Networks

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Advances in Neural Networks – ISNN 2018 (ISNN 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10878))

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Abstract

Streaming recurrent neural networks with linear and spiral space-time structures are analyzed. Formal aspects of the construction and operation of such networks are considered. Four types of synapses are identified in such networks. One of them is the track synapses, which ensure the advancement of signals over the network. Three other types are synapses of dynamic memory. Additionally to traditional synapse weights the attenuation functions of diverging and converging signals are taken into account. The results of simulation of signal processing by streaming recurrent networks with different structures of their layers are presented.

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Authors and Affiliations

  1. St. Petersburg Institute for Informatics and Automation of Russian Academy of Sciences, 14 Liniya 39, St. Petersburg, 199178, Russia

    Vasiliy Osipov & Viktor Nikiforov

Authors
  1. Vasiliy Osipov
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  2. Viktor Nikiforov
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Corresponding author

Correspondence to Viktor Nikiforov .

Editor information

Editors and Affiliations

  1. Texas A&M University at Qatar, Doha, Qatar

    Tingwen Huang

  2. Sichuan University, Chengdu, China

    Jiancheng Lv

  3. Southeast University, Nanjing, China

    Changyin Sun

  4. United Institute of Informatics Problems, Minsk, Belarus

    Alexander V. Tuzikov

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Osipov, V., Nikiforov, V. (2018). Formal Aspects of Streaming Recurrent Neural Networks. In: Huang, T., Lv, J., Sun, C., Tuzikov, A. (eds) Advances in Neural Networks – ISNN 2018. ISNN 2018. Lecture Notes in Computer Science(), vol 10878. Springer, Cham. https://doi.org/10.1007/978-3-319-92537-0_4

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  • DOI: https://doi.org/10.1007/978-3-319-92537-0_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92536-3

  • Online ISBN: 978-3-319-92537-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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