Understanding the Resistive Switching Behaviors of Top Electrode (Au, Cu, and Al)-Dependent TiO-Based Memristive Devices.

Memristor-based neuromorphic computing is promising toward their potential application of handling complex parallel tasks in the period of big data. To implement brain-inspired applications of spiking neural networks, new physical architecture designs are needed. Here, a serial memristive structure (SMS) consisting of memristive devices with different top electrodes is proposed.