Abstract: Traditional vital sign monitoring devices typically involve direct contact with the skin using electrodes, making them unsuitable for daily vital sign monitoring due to the discomfort and ...

Abstract: The development of space-air-ground integrated networks (SAGIN) requires sophisticated satellite Internet emulation tools that can handle complex, dynamic topologies and offer in-depth ...

Abstract: Lithium-ion batteries serve as vital power sources across various industrial sectors, necessitating accurate modeling and state monitoring via battery management systems to ensure reliable ...

Abstract: This extensively revised edition of the bestselling Artech House book, RF Power Amplifiers for Wireless Communications, offers you a comprehensive, practical, and up-to-date understanding of ...

Abstract: While rehabilitation exoskeletons have been extensively studied, systematic design principles for effectively addressing heterogeneous bilateral locomotion in hemiplegia patients are poorly ...

Abstract: A resonant converter is a type of electric power converter that contains a network of inductors and capacitors called a "resonant tank", tuned to resonate at a specific frequency. They find ...

Abstract: Recent years have witnessed the success of deep networks in compressed sensing (CS), which allows for a significant reduction in sampling cost and has gained growing attention since its ...

Abstract: To ensure the thriving development of low-altitude economy, countering unauthorized unmanned aerial vehicles (UAVs) is an essential task. The existing widely deployed base stations hold ...

Abstract: We report the recent progress of waveguide-coupled O-band GeSi quantum confined stark effect electroabsorption modulators, monolithically integrated in a Si photonics platform on 300 mm ...

Abstract: This paper addresses the tracking control problem of uncertain nonlinear strict-feedback systems. Firstly, to enhance the tracking performance of control system, an improved prescribed ...

Abstract: With extensive pretrained knowledge and high-level general capabilities, large language models (LLMs) emerge as a promising avenue to augment reinforcement learning (RL) in aspects, such as ...