Cellular neural networks with memristive cell devices

In this paper, we present simulation measurements of a memristor crossbar device. We designed a PCB memristor package and the appropriate measurement board. Technical details of these circuits are presented. Cellular like topology of this crossbar device can provide high density and local connectivity. We gave a formula to evaluate the direction of the change of the states of the memristor array in case of a given voltage input. Our simulation results show that a memristor crossbar can be a trainable weight-matrix of a fully connected neural network if the memristors have ohmic non-linearity.