Time-varying data processing with nonvolatile memristor-based temporal kernel

Abstract Recent advances in reservoir computing (RC) using memristors have made it possible to perform complicated timing-related recognition tasks using simple hardware. However, the fixed reservoir dynamics in previous studies have severely limited application fields. In this study, RC was implemented with a reservoir that consisted of a W/HfO2/TiN memristor (M), a capacitor (C), and a resistor (R), in which the reservoir dynamics could be arbitrarily controlled by changing their parameters. After the capability of the RC to identify the static MNIST data set was proven, the system was adopted to recognize the sequential data set [ultrasound (malignancy of lesions) and electrocardiogram (arrhythmia)] that had a significantly different time constant (107 vs. 1 s). The suggested RC system feasibly performed the tasks by simply varying the C and R, while the M remained unvaried. These functionalities demonstrate the high adaptability of the present RC system compared to the previous ones.