Abstract: In this paper, Nash equilibrium seeking among a network of players is considered. Different from many existing works on Nash equilibrium seeking in noncooperative games, the players ...

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: In recent years, the digital world has advanced significantly, particularly on the Internet, which is critical given that many of our activities are now conducted online. As a result of ...

Abstract: Medical image segmentation is an important step in medical image analysis. With the rapid development of a convolutional neural network in image processing, deep learning has been used for ...

Abstract: In this article, based on the LLC resonant converter fundamental harmonic analysis model, the modulation strategies for LLC resonant converter can be categorized into the following three ...

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: 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: Recently, several indoor localization solutions based on WiFi, Bluetooth, and UWB have been proposed. Due to the limitation and complexity of the indoor environment, the solution to achieve ...

Abstract: The interdependence of different energy forms in multiple energy systems (MESs) could leverage their synergies to reduce carbon emissions. However, such synergies cannot be exploited without ...

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: Current approaches for visual-inertial odometry (VIO) are able to attain highly accurate state estimation via nonlinear optimization. However, real-time optimization quickly becomes ...

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