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Study of Chaos in a Simple Discrete Recurrence Neural Network

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Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence (IWANN 2001)

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Abstract

A simple class of discrete recurrent neural network is analyzed to establish its possible chaotic dynamics. A two-neuron network is selected for simplicity and two cases of chaotic dynamics are distinguised, one degenerate (one-dimensional) and a more general situation with a two-dimensional attractor. The robustness of the found configuations is assessed through evaluation of Lyapunov exponents ia a range of parameter values. In every situation there is a lack of robustness, as suggested in a conjecture of Barreto et al.

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Author information

Authors and Affiliations

  1. Department of Applied Physics, University of La Laguna, La Laguna, 38271, Tenerife, Spain

    Jose D. Piñeiro, Roberto L. Marichal, Lorenzo Moreno, Jose F. Sigut & Evelio J. González

Authors
  1. Jose D. Piñeiro
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  2. Roberto L. Marichal
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  3. Lorenzo Moreno
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  4. Jose F. Sigut
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  5. Evelio J. González
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Editor information

Editors and Affiliations

  1. Departamento de Inteligencia Artificial Sanda del Rey, Universidad Nacional de Educación a Distancia, s/n., Madrid, 28040, Spain

    José Mira

  2. Departamento de Arquitectura y Tecnología de Computadores, Universidad de Granada, Campus Fuentenueva, 18071, Granada, Spain

    Alberto Prieto

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© 2001 Springer-Verlag Berlin Heidelberg

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Piñeiro, J.D., Marichal, R.L., Moreno, L., Sigut, J.F., González, E.J. (2001). Study of Chaos in a Simple Discrete Recurrence Neural Network. In: Mira, J., Prieto, A. (eds) Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence. IWANN 2001. Lecture Notes in Computer Science, vol 2084. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45720-8_69

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  • DOI: https://doi.org/10.1007/3-540-45720-8_69

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42235-8

  • Online ISBN: 978-3-540-45720-6

  • eBook Packages: Springer Book Archive

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