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Storage Capacities of Twin-Multistate Quaternion Hopfield Neural Networks
A twin-multistate quaternion Hopfield neural network (TMQHNN) is a multistate Hopfield model and can store multilevel information, such as image data. Storage capacity is an important problem of Hopfield neural networks. Jankowski et al. approximated the crosstalk terms of complex-valued Hopfield ne...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Hindawi
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6236997/ https://www.ncbi.nlm.nih.gov/pubmed/30515194 http://dx.doi.org/10.1155/2018/1275290 |
Sumario: | A twin-multistate quaternion Hopfield neural network (TMQHNN) is a multistate Hopfield model and can store multilevel information, such as image data. Storage capacity is an important problem of Hopfield neural networks. Jankowski et al. approximated the crosstalk terms of complex-valued Hopfield neural networks (CHNNs) by the 2-dimensional normal distributions and evaluated their storage capacities. In this work, we evaluate the storage capacities of TMQHNNs based on their idea. |
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