Abstract
A neuron, as it was discussed in Chap. 2, is a biological cell that has complex structure. Furthermore, numerous processes occur within it. Therefore, at the present level of scientific knowledge it is impossible to create any formal model that contains all the structural and dynamical aspects of the neuron. In such a situation two approaches can be applied: either a very simplified model of the neuron is created or there is created a model which describes only a part of a neuron structures or processes. The first group of the models is widely used as the basis for artificial neural networks. The second group of the models is frequently embodied as electronic circuits. Such an approach creates good perspectives for using the electronic circuits in future as the components of more holistic models of the neuron and, as the consequence, as the basis of artificial neural networks. In this chapter both groups of models are discussed. Connections with electronic circuits are presented as well.
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Bielecki, A. (2019). Models of the Whole Neuron. In: Models of Neurons and Perceptrons: Selected Problems and Challenges. Studies in Computational Intelligence, vol 770. Springer, Cham. https://doi.org/10.1007/978-3-319-90140-4_6
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DOI: https://doi.org/10.1007/978-3-319-90140-4_6
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Publisher Name: Springer, Cham
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