The Interconnection Tensor Rank and the Neural Network Storage Capacity

Boris V. Kryzhanovsky

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arXiv · 2504.05926

The Interconnection Tensor Rank and the Neural Network Storage Capacity

Boris V. Kryzhanovsky

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Abstract

Neural network properties are considered in the case of the interconnection tensor rank being higher than two. This sort of interconnection tensor occurs in realization of crossbar-based neural networks. It is intrinsic for a crossbar design to suffer from parasitic currents. It is shown that the interconnection tensor of a certain form makes the neural network much more efficient: the storage capacity and basin of attraction of the network increase considerably. A network like the Hopfield one is used in the study.

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Boris V. Kryzhanovsky. 2025-04-08. The Interconnection Tensor Rank and the Neural Network Storage Capacity. https://arxiv.org/abs/2504.05926

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