Abstract
As is well-known, a natural neuron is made up of a huge number of biomolecules from a nanoscopic point of view. A conventional ‘artificial neural network’ (ANN) [1] consists of nodes with static functions, but a more realistic model for the brain could be implemented with functional molecular agents which move around the neural network and cause a change in the neural functionality.
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Suzuki, H., Ohsaki, H., Sawai, H. (2010). A Network-Based Computational Model with Learning. In: Calude, C.S., Hagiya, M., Morita, K., Rozenberg, G., Timmis, J. (eds) Unconventional Computation. UC 2010. Lecture Notes in Computer Science, vol 6079. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13523-1_26
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DOI: https://doi.org/10.1007/978-3-642-13523-1_26
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