Abstract: A dual-operation-mode ring oscillator that employs dual-delay paths is presented. The two operation modes, referred to as the differential and common modes, have different output waveform ...
Abstract: Recently, deep-learning-based fault diagnosis methods have been widely studied for rolling bearings. However, these neural networks are lack of interpretability for fault diagnosis tasks.
Abstract: This article presents a hybrid trajectory optimization method designed to generate collision-free, smooth trajectories for autonomous mobile robots. By combining sampling-based model ...
Abstract: In this paper, we study the secrecy performance of mixed radio-frequency (RF) - free space optical (FSO) systems by considering both RF and FSO eavesdropper attacks. More precisely, we shed ...
Abstract: A K-/Ka-band shared-aperture endfire phased array antenna is presented in this article. The antenna has the properties of dual wide bandwidths, orthogonal circular polarizations (CPs), wide ...
Abstract: The operation of wireless power transfer systems with multiple transmitters (TXs) or receivers (RXs) is investigated. With multiple TXs or RXs in a limited space, couplings occur between TXs ...
Abstract: Prognostics and health management applications rely heavily on predicting industrial equipment’s remaining useful life (RUL). The traditional RUL prediction approaches mainly consider the ...
Abstract: We present a review of 3D point cloud processing and learning for autonomous driving. As one of the most important sensors in autonomous vehicles (AVs), lidar sensors collect 3D point clouds ...
Abstract: Classroom learning behavior recognition can provide effective technical support for teaching and learning. However, in natural classroom teaching scenarios, classroom learning behaviors are ...
Abstract: Field-programmable gate arrays (FPGAs) have been shown to provide high computational density and efficiency for many computing applications by allowing circuits to be customized to any ...
Abstract: For multi-view convolutional neural network based 3D object recognition, how to fuse the information of multiple views is a key factor affecting the recognition performance. Most traditional ...
Abstract: This paper presents an advanced deep ensemble learning framework for short-term load forecasting (STLF). The refined deep ensemble model (DEM), complemented ...