Summary. Recent discoveries in neuroscience imply that the basic computational elements are the dendrites that make up more than 50% of a cortical neuron’s membrane. Neuroscientists now believe that the basic computation units are dendrites, capable of computing simple logic functions. This paper discusses two types of neural networks that take advantage of these new discoveries. The focus of this paper is on some learning algorithms in the two neural networks. Learning is in terms of lattice computations that take place in the dendritic structure as well as in the cell body of the neurons used in this model.
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© 2007 Springer-Verlag Berlin Heidelberg
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Ritter, G.X., Urcid, G. (2007). Learning in Lattice Neural Networks that Employ Dendritic Computing. In: Kaburlasos, V.G., Ritter, G.X. (eds) Computational Intelligence Based on Lattice Theory. Studies in Computational Intelligence, vol 67. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72687-6_2
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DOI: https://doi.org/10.1007/978-3-540-72687-6_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72686-9
Online ISBN: 978-3-540-72687-6
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