Abstract
This paper reports a study on spike-timing-dependent plasticity (STDP) in high-k metal gate (HKMG) based ferroelectric Field effect transistors (FeFET). FeFET devices have been fairly well exploited in the context of in-memory computing due to their excellent non-volatile storage characteristics and analog conductance tunability. However, applications of FeFET devices in Spiking Neural Networks (SNN) are yet to be explored properly. This work reports the potential of HfO 2 based HKMG-FeFET synapses for SNN hardware by demonstrating energy-efficient STDP learning.