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arXiv · 2101.05247

Recognition Capabilities of a Hopfield Model with Auxiliary Hidden Neurons

Marco Benedetti·Victor Dotsenko·Giulia Fischetti·Enzo Marinari·Gleb Oshanin
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Abstract

We study the recognition capabilities of the Hopfield model with auxiliary hidden layers, which emerge naturally upon a Hubbard-Stratonovich transformation. We show that the recognition capabilities of such a model at zero-temperature outperform those of the original Hopfield model, due to a substantial increase of the storage capacity and the lack of a naturally defined basin of attraction. The modified model does not fall abruptly in a regime of complete confusion when memory load exceeds a sharp threshold.

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Marco Benedetti, Victor Dotsenko, Giulia Fischetti, Enzo Marinari, Gleb Oshanin. 2021-01-13. Recognition Capabilities of a Hopfield Model with Auxiliary Hidden Neurons. https://doi.org/10.1103/physreve.103.l060401

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