Zobrazeno 1 - 10
of 28
pro vyhledávání: '"TingPeng Li"'
Publikováno v:
IEEE Access, Vol 12, Pp 136502-136514 (2024)
In causal learning, discovering the causal graph of the underlying generative mechanism from observed data is crucial. However, real-world data for causal discovery is scarce and expensive, leading researchers to rely on synthetic datasets, which may
Externí odkaz:
https://doaj.org/article/0d9c60d322634aca864dcaa6e72f88f9
Publikováno v:
IEEE Access, Vol 9, Pp 124425-124433 (2021)
The recent years has witnessed a rapid development of Deep Learning (DL) based Automation Modulation Classification (AMC) methods, which has proved to outperform traditional classification approaches. In order to disturb the deep neural networks for
Externí odkaz:
https://doaj.org/article/342cc6039f0f494184cd78a6034ab81a
Publikováno v:
IEEE Access, Vol 8, Pp 214504-214519 (2020)
Evaluating the effect of blanket jamming is at the core of performance analysis and jamming/anti-jamming design for radar. Restricted to diverse jamming types and radar's applications, it is challenging to put forward a unified framework for quantita
Externí odkaz:
https://doaj.org/article/9edf41651eea43f5a85a53a438fa04a6
Publikováno v:
Micromachines, Vol 14, Iss 2, p 426 (2023)
An analytically separated neuro-space mapping (Neuro-SM) model of power transistors is proposed in this paper. Two separated mapping networks are introduced into the new model to improve the characteristics of the DC and AC, avoiding interference of
Externí odkaz:
https://doaj.org/article/a80ae98168b2423ab8474171277fea33
Publikováno v:
The Journal of Engineering (2019)
For passive bistatic radar (PBR), it is convenient to use software method to realise the signal processing. However, because of the huge amount of data computing, it is difficult to achieve the real-time signal processing by software method only with
Externí odkaz:
https://doaj.org/article/dca1716c8e534c4682b0ebc15baab855
Autor:
Yang YANG, Tingpeng LI, Xiaomin CHEN, Manxi WANG, Qiuming ZHU, Ruirui FENG, Fuqiao DUAN, Taotao ZHANG
Publikováno v:
Chinese Journal of Aeronautics. 35:106-116
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ba06974f74793a5a31ce5dd63fbc41d0
https://doi.org/10.1016/j.cja.2021.12.008
https://doi.org/10.1016/j.cja.2021.12.008
Autor:
Baofeng Ji, Yifan Liu, Tingpeng Li, Ling Xing, Weixing Wang, Mumtaz, Shahid, Xiaolong Shang, Wanying Liu, Congzheng Han
Publikováno v:
CMES-Computer Modeling in Engineering & Sciences; 2024, Vol. 138 Issue 1, p679-689, 11p
Publikováno v:
IEEE Sensors Journal. 21:15153-15160
Radar jamming effect analysis (RJEA) is important for improving the performance of radar sensors in jamming environments and one of the most popular methods for RJEA is Bayesian inference network (BIN). Notice the features in RJEA are usually continu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a862b2fb53ace2e8281cc6f07ce920a0
https://doi.org/10.1109/jsen.2021.3072624
https://doi.org/10.1109/jsen.2021.3072624
Publikováno v:
IEEE Access, Vol 9, Pp 124425-124433 (2021)
The recent years has witnessed a rapid development of Deep Learning (DL) based Automation Modulation Classification (AMC) methods, which has proved to outperform traditional classification approaches. In order to disturb the deep neural networks for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::71429cc8edcb0ef45bc1aa432e56ecad
https://ieeexplore.ieee.org/document/9520398/
https://ieeexplore.ieee.org/document/9520398/
Publikováno v:
Progress In Electromagnetics Research Letters. 91:9-16
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::545432d5e4ed9c564488642be0c90a4c
https://doi.org/10.2528/pierl20030405
https://doi.org/10.2528/pierl20030405