Fully hardware-implemented memristor convolutional neural network

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A compute-in-memory chip based on resistive random-access memory (2022, positive): “…results using a mixture of hardware characterization and software simulation, for example, emulate the array-level MVM process in software using measured device characteristics 3,5,21,24 , such an approach often fails to model the complete set of non-idealities existing in realistic hardware.”
A crossbar array of magnetoresistive memory devices for in-memory computing (2022, background): “Of the four NVMs that can be produced at volume—that is, resistive random-access memory 8–13 , phase-change random-access memory 14,15 , flash memory 16–19 and spin-transfer-torque magnetoresistive random-access memory (STT-MRAM, or MRAM for brevity) 20–22,25 , Here we fill this gap and implement…”
In-sensor reservoir computing system for latent fingerprint recognition with deep ultraviolet photo-synapses and memristor array (2022, methodology): “1c. Memristors feature excellent adjustable resistive state characteristics and naturally perform the vector-matrix multiplication in an array structure, making it suitable to serve as readout layer 36 – 38 , as shown in the right panel of Fig.”
Experimental photonic quantum memristor (2021, background): “[31] Peng Yao, Huaqiang Wu, Bin Gao, Jianshi Tang, Qingtian Zhang, Wenqiang Zhang, J Joshua Yang, and He Qian, “Fully hardware-implemented memristor convolutional neural network,” Nature 577, 641–646 (2020).”