Abstract: Image processing algorithms continue to demand higher performance from computers. However, computer performance is not improving at the same rate as before. In response to the current ...

Abstract: With the expansive deployment of ground base stations, low Earth orbit (LEO) satellites, and aerial platforms such as unmanned aerial vehicles (UAVs) and high altitude platforms (HAPs), the ...

Abstract: Deep learning, as an important branch of machine learning, has been widely applied in computer vision, natural language processing, speech recognition, and more. However, recent studies have ...

Abstract: Wearable ultrasound has been widely developed for long-term, continuous imaging without the need for bulky system manipulation and repeated manual locating. To potentially lead to more ...

Abstract: Blockchain sharding is a significant technical area, improving the scalability of blockchain systems. It is regarded as one of the potential solutions that can achieve on-chain scaling, and ...

Abstract: For quaternion-based spacecraft attitude tracking control, most existing prescribed performance control (PPC) schemes require that the scalar part of the ...

Abstract: Unmanned Aerial Vehicles (UAVs) can be employed as short-term aerial base stations or as access points for User Equipments (UEs) to communicate with other UEs effectively. However, ...

Abstract: A form of circuit which is of considerable interest for the transmission of high frequency currents is one consisting of a cylindrical conducting tube within which a smaller conductor is ...

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=5 ...

Abstract: Industrial time-sensitive networking (TSN) is pivotal for ensuring real-time and reliable flow transmission. There is a growing focus on its scalable scheduling for time-critical flows ...

Abstract: In this article, an adaptive prescribed-time neural controller is developed for the tracking problem of a class of high-order nonlinear systems with full-state constraints. First, a ...

Abstract: Industrial time series prediction (ITSP) is critical to the predictive maintenance system of modern industry. However, time-varying conditions and complex industrial processes cause the ...