In‐Depth Analysis of One Selector–One Resistor Crossbar Array for Its Writing and Reading Operations for Hardware Neural Network with Finite Wire Resistance

This work provides a comprehensive analytical analysis of one‐selector‐one‐resistor (1S1R) crossbar array (CBA) device for hardware neural network (HNN) applications. Simplified models are prepared from particular 1S1R to validate the analysis. The read margin (RM) results show that V /3 voltage scheme and reduced selector leakage necessary maximize RM maximum operable size N CBA, where indicates number wires (word line or bit line). write (WM) unwanted switching unselected cell during operation is unlikely in CBA even with large value, despite drop along interconnection wire. simultaneous multiply‐and‐accumulate operations conducted using method examine influence according wire memory cells HNN Reducing resistance on‐state conductance increases available value when operates near threshold conditions. proposed model can estimate accuracy degradation through involvement unintentional drop.