Zobrazeno 1 - 10
of 78
pro vyhledávání: '"Gao Jingkun"'
Publikováno v:
Tongxin xuebao, Vol 45, Pp 166-179 (2024)
Aiming at the problem that the existing federated learning schemes cannot adaptively defend Byzantine attacks and low model accuracy, a secure federated learning scheme based on adaptive Byzantine defense was proposed. Through adaptive preliminary ag
Externí odkaz:
https://doaj.org/article/67ac0a35b9584e4baabf4003c048becb
Publikováno v:
Leida xuebao, Vol 7, Iss 6, Pp 676-684 (2018)
Near-field 3-D imaging based on a scanning array is an important application of Synthetic Aperture Radar (SAR) 3-D imaging technology for civil use. Compared with Single-Input-Single-Output (SISO) arrays, a Multi-Input-Multi-Output (MIMO) scanning sy
Externí odkaz:
https://doaj.org/article/a843186a2ec2400b8325be433e84f2c1
Publikováno v:
Leida xuebao, Vol 7, Iss 1, Pp 97-107 (2018)
Echo simulation is a precondition for developing radar imaging systems, algorithms, and subsequent applications. Electromagnetic scattering modeling of the target is key to echo simulation. At terahertz (THz) frequencies, targets are usually of ultra
Externí odkaz:
https://doaj.org/article/2a7bfc5b885d44938f56756b98224396
Publikováno v:
In Engineering Structures 1 January 2025 322 Part B
Publikováno v:
International Journal of Production Research; Jul2024, Vol. 62 Issue 13, p4776-4792, 17p
Deep learning performs remarkably well on many time series analysis tasks recently. The superior performance of deep neural networks relies heavily on a large number of training data to avoid overfitting. However, the labeled data of many real-world
Externí odkaz:
http://arxiv.org/abs/2002.12478
The monitoring and management of numerous and diverse time series data at Alibaba Group calls for an effective and scalable time series anomaly detection service. In this paper, we propose RobustTAD, a Robust Time series Anomaly Detection framework b
Externí odkaz:
http://arxiv.org/abs/2002.09545
Extracting the underlying trend signal is a crucial step to facilitate time series analysis like forecasting and anomaly detection. Besides noise signal, time series can contain not only outliers but also abrupt trend changes in real-world scenarios.
Externí odkaz:
http://arxiv.org/abs/1906.03751
Decomposing complex time series into trend, seasonality, and remainder components is an important task to facilitate time series anomaly detection and forecasting. Although numerous methods have been proposed, there are still many time series charact
Externí odkaz:
http://arxiv.org/abs/1812.01767
Akademický článek
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