Abstract: Terahertz technology applications, sensors, and sources are briefly reviewed. Emphasis is placed on the less familiar components, instruments, or subsystems. Science drivers, some historical ...

Abstract: A new framework is developed for control of constrained nonlinear systems with structured parametric uncertainty. Forward invariance of a safe set is achieved through online parameter ...

Abstract: This article studies a prescribed performance adaptive robust control (PPARC) scheme for uncertain robotic manipulators. First, a state transformation is introduced to embed the predefined ...

Abstract: We investigate the performance and design of free-space optical (FSO) communication links over slow fading channels from an information theory perspective. A statistical model for the ...

Abstract: Balancing convergence and diversity plays a key role in evolutionary multiobjective optimization (EMO). Most current EMO algorithms perform well on problems with two or three objectives, but ...

Abstract: Large Language Models (LLMs) recently demonstrated extraordinary capability in various natural language processing (NLP) tasks including language translation, text generation, question ...

Abstract: Implementation of backstepping becomes increasingly complex as the order of the system increases. This increasing complexity is mainly driven by the need to compute command derivatives at ...

Abstract: 3D Gaussian Splatting (3DGS) has emerged as a prominent technique with the potential to become a mainstream method for 3D representations. It can effectively transform multi-view images into ...

Abstract: Deep generative models have unlocked another profound realm of human creativity. By capturing and generalizing patterns within data, we have entered the epoch of all-encompassing Artificial ...

Abstract: This article surveys recent progress and discusses future opportunities for simultaneous localization and mapping (SLAM) in extreme underground environments. SLAM in subterranean ...

Abstract: Compute-in-memory (CIM) is a new computing paradigm that addresses the memory-wall problem in hardware accelerator design for deep learning. The input vector and weight matrix multiplication ...

Impact Statement: AI ethics is an important emerging topic among academia, industry, government, society, and individuals. In the past decades, many efforts have been made to study the ethical issues ...