Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Yuebin CHEN"'
Publikováno v:
IEEE Access, Vol 9, Pp 6201-6212 (2021)
Transfer learning is a promising approach for reducing training time in a brain-computer interface (BCI). However, how to effectively transfer data from previous users to a new user poses a huge challenge. This paper presents a novel transfer learnin
Externí odkaz:
https://doaj.org/article/65955af6a91e4f8bb23f66339386bc1d
Publikováno v:
Dianxin kexue, Vol 34, Pp 129-135 (2018)
Aiming at stochastic probabilistic SSDF attacks,a variable threshold energy detection algorithm based on trust degree was proposed.Firstly,the variable threshold was updated by comparing the actual fusion value with the upper and lower boundary value
Externí odkaz:
https://doaj.org/article/678603c6d34e43c097e07c371d4b90b0
Publikováno v:
Sensors, Vol 16, Iss 4, p 442 (2016)
In a passive ultra-high frequency (UHF) radio-frequency identification (RFID) system, tag collision is generally resolved on a medium access control (MAC) layer. However, some of collided tag signals could be recovered on a physical (PHY) layer and,
Externí odkaz:
https://doaj.org/article/6491fc9aca0f4436a58e80626b473cab
Autor:
haowei huang, huijuan zhang, pengfei li, yuebin chen, shuanzhu zhao, xiaotong sun, Hong-Guang Piao, xia zhao, Yanliang Huang
Publikováno v:
CORROSION.
With the rapid development of modern civilization, the development of Marine resources has become imminent, but seawater corrosion has become one of the most important factors hindering development. In order to overcome this problem, an environment-f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b6f79756ce844c223cc7e120eb05f726
https://doi.org/10.5006/4285
https://doi.org/10.5006/4285
Publikováno v:
IEEE Access, Vol 9, Pp 6201-6212 (2021)
Transfer learning is a promising approach for reducing training time in a brain-computer interface (BCI). However, how to effectively transfer data from previous users to a new user poses a huge challenge. This paper presents a novel transfer learnin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a1083f613c21519833c3c416cd63c7b7
https://doi.org/10.1109/access.2020.3048683
https://doi.org/10.1109/access.2020.3048683
Publikováno v:
ICSAI
Spectrum sensing is one of the key technologies of cognitive radio. Energy detection is widely used in spectrum sensing, but noise uncertainty and low signal-to-noise ratio seriously affects its detection performance. A system model based on noise un
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2c84fca948258200b84a93c36ef306a8
https://doi.org/10.1109/icsai.2018.8599342
https://doi.org/10.1109/icsai.2018.8599342
Publikováno v:
EMS
As for nonstationary signal, such as subpixel peak detection,we could be difficult to suppress the noise of super- Gaussian and sub-Gaussian in the mixed signal with the traditional low order filter. The gradient search method is generally adopt in t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fe9937b309fd634c5c1f504328462743
https://doi.org/10.1109/ems.2016.023
https://doi.org/10.1109/ems.2016.023
Publikováno v:
ICIA
In the cognitive radio network, to be directed against the primary user emulation attack(PUEA), in this paper, an improved energy detection algorithm is used in cooperative spectrum sensing(CSS) technology to improve the systematic performance. Suppo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c8c06bee50287edab0cc164881752ece
https://doi.org/10.1109/icinfa.2016.7832158
https://doi.org/10.1109/icinfa.2016.7832158
Publikováno v:
CITS
In the cognitive radios (CR), there is a security issue-spectrum sensing data falsification attacks (SSDF) in the process of cooperation. Some malicious users (MUs) who unwilling to cooperate friendly with other users may launch SSDF attacks by falsi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::64aed09ac5f80ec0ef61da04a737a888
https://doi.org/10.1109/cits.2016.7546433
https://doi.org/10.1109/cits.2016.7546433
Publikováno v:
CITS
The framework of the ScSPM (Spatial Pyramid matching method using Sparse Coding) model is concise, but a good performance in scene classification is achieved. However, its performance can not be significantly improved duo to the limited discriminativ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6092de29b8b0053fd74576df91aea7cc
https://doi.org/10.1109/cits.2016.7546458
https://doi.org/10.1109/cits.2016.7546458