A memristor-array Hopfield network uses device nonlinearity to exceed classical memory capacity with K ~ 0.14N experimentally and superlinear K ~ 0.3 N^1.2 in simulations.
Specifically, the learned W and b are chosen such that each stored pattern approximately satisfies the fixed-point relation in its linearized form
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A Hardware-aware Hopfield Network with a Nonlinear Memristor Array for Robust Associative Memory with Superlinear Capacity
A memristor-array Hopfield network uses device nonlinearity to exceed classical memory capacity with K ~ 0.14N experimentally and superlinear K ~ 0.3 N^1.2 in simulations.