Abstract: Conventional noise estimation methods for arrayed microelectromechanical system (MEMS) inertial measurement units (MIMUs) exhibit reduced effectiveness in dynamic scenarios, leading to ...

Abstract: We present MEMprop, the adoption of gradient-based learning to train fully memristive spiking neural networks (MSNNs). Our approach harnesses intrinsic device dynamics to trigger naturally ...