Molecular approach to hopfield neural network

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Abstract

The present article puts forward a completely new technology development, a spin glass-like molecular implementation of the Hopfield neural structure. This novel approach uses magnetic molecules homogenously distributed in mesoporous silica matrix, which forms a base for a converting unit, an equivalent of a neuron in the Hopfield network. Converting units interact with each other via a fully controlled magnetic fields, which corresponds to weighted interconnections in the Hopfield network. This novel technology enables building fast, high-density content addressable associative memories. In particular, it is envisaged that in the future this approach can be scaled up to mimic memory with human-like characteristics. This would be a breakthrough in artificial brain implementations and usher in a new type of highly intelligent beings. Another application relates to systems designed for multi-objective optimization (multiple criteria decision making).

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Laskowski, Ł., Laskowska, M., Jelonkiewicz, J., & Boullanger, A. (2015). Molecular approach to hopfield neural network. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 9119, pp. 72–78). Springer Verlag. https://doi.org/10.1007/978-3-319-19324-3_7

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