A higher number of unique conductance levels in the memristor crossbar node ensures higher accuracy for analogue dot-product computations. Series and parallel combinations of memristors are used as a common approach to creating multilevel conductance superresolution nodes. The super-resolution nodes are tolerant to a wide range of memristor non-idealities. In this paper, we present a bridge-type design of a super-resolution node. Compared to previous work, the proposed design could achieve a resolution improvement of 5 to 9 times higher when individual memristor conductance levels change from 5 to 12 states. Although the bridge nodes preserve tolerance to memristor variability similar to that of a parallel superresolution node, they do so at lower area and power requirements. Bridge-based crossbar nodes were successfully tested in artificial and convolutional neural networks, showing near-idealistic inference accuracy. 

A. Radhakrishnan, S. Pallathuvalappil, B. Choubey and A. James, "Bridge Memristor Super-Resolution Crossbars," in IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 12, no. 4, pp. 944-951, Dec. 2022, doi: 10.1109/JETCAS.2022.3221539.