Sparse coding with memristor networks.

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In-memory computing with resistive switching devices (2018, background): “Crosspoint MVM can be adopted for a broad range of problems, including image compression 91 , sparse coding 93 , and implementation of artificial neural networks (ANNs), where G ij has the meaning of a synaptic weight, V j is a pre-synaptic spike amplitude, and I i is the input signal to the i th…”
Implementation of multilayer perceptron network with highly uniform passive memristive crossbar circuits (2017, unknown): “For example, an analog tuning was essential for other demonstrations based on passive memristive circuits, though was performed with much cruder precision 19,39 .”
Efficient and self-adaptive in-situ learning in multilayer memristor neural networks (2018, methodology): “…for other applications, by device engineering for better IV linearity 37,38 , or using pulse width instead of amplitude to represent analog input (with increased time overhead) 27,28,37 , or employing multiple memristors to represent one synaptic weight (at the expense of chip area) 52 , etc.”