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. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Isokawa, T., Nishimura, H., Kamiura, N., & Matsui, N. (2007). Dynamics of discrete-time quaternionic hopfield neural networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4668 LNCS, pp. 848–857). Springer Verlag. https://doi.org/10.1007/978-3-540-74690-4_86
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