Abstract
We analyze a discrete-time quaternionic Hopfield neural network with continuous state variables updated asynchronously. The state of a neuron takes quaternionic value which is four-dimensional hypercomplex number. Two types of the activation function for updating neuron states are introduced and examined. The stable states of the networks are demonstrated through an example of small network.
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© 2007 Springer-Verlag Berlin Heidelberg
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Isokawa, T., Nishimura, H., Kamiura, N., Matsui, N. (2007). Dynamics of Discrete-Time Quaternionic Hopfield Neural Networks. In: de Sá, J.M., Alexandre, L.A., Duch, W., Mandic, D. (eds) Artificial Neural Networks – ICANN 2007. ICANN 2007. Lecture Notes in Computer Science, vol 4668. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74690-4_86
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DOI: https://doi.org/10.1007/978-3-540-74690-4_86
Publisher Name: Springer, Berlin, Heidelberg
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