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International Conference on Artificial Intelligence and Soft Computing

ICAISC 2015: Artificial Intelligence and Soft Computing pp 26–38Cite as

Innovative Types and Abilities of Neural Networks Based on Associative Mechanisms and a New Associative Model of Neurons

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 9119)

Abstract

This paper presents a new concept of representation of data and their relations in neural networks which allows to automatically associate, reproduce them, and generalize about them. It demonstrates an innovative way of developing emergent neural representation of knowledge using a new kind of neural networks whose structure is automatically constructed and parameters are automatically computed on the basis of plastic mechanisms implemented in a new associative model of neurons - called as-neurons. Inspired by the plastic mechanisms commonly occurring in a human brain, this model allows to quickly create associations and establish weighted connections between neural representations of data, their classes, and sequences. As-neurons are able to automatically interconnect representing similar or sequential data. This contribution describes generalized formulas for quick analytical computation of the structure and parameters of ANAKG neural graphs for representing and recalling of training sequences of objects.

Keywords

  • Associative mechanisms
  • As-neurons
  • ANAKG neural graphs
  • Knowledge engineering
  • Knowledge representation
  • Artificial neural associative systems
  • Associative neural networks
  • Emergent cognitive systems

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  • DOI: 10.1007/978-3-319-19324-3_3
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Author information

Authors and Affiliations

  1. Department of Automatics and Biomedical Engineering, AGH University of Science and Technology, Mickiewicza Av. 30, 30-059, Cracow, Poland

    Adrian Horzyk

Authors
  1. Adrian Horzyk
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Corresponding author

Correspondence to Adrian Horzyk .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Częstochowa, Poland

    Rafal Scherer

  4. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

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Horzyk, A. (2015). Innovative Types and Abilities of Neural Networks Based on Associative Mechanisms and a New Associative Model of Neurons. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2015. Lecture Notes in Computer Science(), vol 9119. Springer, Cham. https://doi.org/10.1007/978-3-319-19324-3_3

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  • DOI: https://doi.org/10.1007/978-3-319-19324-3_3

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19323-6

  • Online ISBN: 978-3-319-19324-3

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