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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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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