Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Zehan Wan"'
Publikováno v:
IET Communications, Vol 17, Iss 17, Pp 1955-1961 (2023)
Abstract Clock synchronization is indispensable for numerous applications of wireless sensor networks (WSNs). When no common reference clock is available, the nodes must employ distributed synchronization techniques. This paper proposes, a distribute
Externí odkaz:
https://doaj.org/article/1cce42f2a34545e48e1d5caf2d0a9f59
Publikováno v:
IET Communications, Vol 17, Iss 7, Pp 797-806 (2023)
Abstract In this paper, a joint detection strategy of Willie based on two phases observation is proposed and an energy‐efficient covert communication scheme with an adaptive assist nodes group (AANG) based on uniform jamming power (UJP) strategy is
Externí odkaz:
https://doaj.org/article/b0608daf55364f65b3f8aa7abbacc439
Publikováno v:
Electronics Letters, Vol 58, Iss 19, Pp 743-746 (2022)
Abstract This letter proposes a joint weighted power detector based on maximum a posteriori probability criterion for Willie aiming at two‐hop covert communication scenario, which is a near optimal detector. Instead of only supervising one single p
Externí odkaz:
https://doaj.org/article/35277a6c778640e09a470aeb1f5f9ac0
Publikováno v:
Tongxin xuebao, Vol 43, Pp 123-132 (2022)
The existing embedded scheme requires far lower transmission power of the covert system than that of the host system, and thus decreasing the reliability of covert transmission.To figure out the above limitations, a continuous noise covert communicat
Externí odkaz:
https://doaj.org/article/f39642317f044d7f85aa658542c7d062
Automatic modulation classification (AMC) plays an important role in various applications such as cognitive radio and dynamic spectrum access. Many research works have been exploring deep learning (DL) based AMC, but they primarily focus on single-ca
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c60e6d920bfe8c3eb352b7ccd3324b9b
https://doi.org/10.22541/au.166351508.81958540/v1
https://doi.org/10.22541/au.166351508.81958540/v1
Publikováno v:
Machines, Vol 12, Iss 8, p 565 (2024)
The Virtual Track Train (VTT) represents an innovative urban public transportation system that combines tire-based running gears with rail transit management. Effective control of such a system necessitates precise state estimation, a task rendered c
Externí odkaz:
https://doaj.org/article/bf3e9794534a4c45ac005c23d1ca1672
Publikováno v:
Applied Sciences, Vol 13, Iss 14, p 8443 (2023)
The virtual track train (VTT) is a new urban public transportation system that adopts all-axle steering and distributed drive. The Super autonomous Rail rapid Transit (SRT), as one of them, adopts a four-module six-axle structure. In response to its
Externí odkaz:
https://doaj.org/article/6197e79fa9594ce5bfd22071f5b01cdf
Autor:
Caiguo Liu, Wentao Yu, Chunping Cai, Shijian Huang, Huanghua Wu, Zehan Wang, Pan Wang, Yucheng Zheng, Pengjie Wang, Naixing Ye
Publikováno v:
Horticulturae, Vol 8, Iss 10, p 932 (2022)
Wuyi Mountain in Southeast China is the origin of black tea and oolong tea. It is also considered the ‘treasure trove of tea cultivars’ because of its rich tea germplasm resources. In the present study, the population structure and genetic divers
Externí odkaz:
https://doaj.org/article/172fd2d4541447c1b13f3ea58e1bc607
Publikováno v:
Sensors, Vol 22, Iss 11, p 4295 (2022)
Accurate trajectory prediction is an essential task in automated driving, which is achieved by sensing and analyzing the behavior of surrounding vehicles. Although plenty of research works have been invested in this field, it is still a challenging s
Externí odkaz:
https://doaj.org/article/19b0be1460f74ec2b46bbb3a6d4309b1
Publikováno v:
Remote Sensing, Vol 13, Iss 19, p 3876 (2021)
Ground-based cloud images can provide information on weather and cloud conditions, which play an important role in cloud cover monitoring and photovoltaic power generation forecasting. However, the cloud motion prediction of ground-based cloud images
Externí odkaz:
https://doaj.org/article/35adb41ab1004ae8bb4e28be87ea48c4