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湖南大学 [21]
北京航空航天大学 [17]
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期刊论文 [124]
会议论文 [7]
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2019 [131]
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Prediction error analysis of wind power based on clustering and non-parametric kernel density estimation
期刊论文
Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2019, 卷号: 40, 期号: 12, 页码: 3594-3604
作者:
Zhang, Xiaoying
;
Zhang, Xiaomin
;
Liao, Shun
;
Chen, Wei
;
Wang, Xiaolan
收藏
  |  
浏览/下载:17/0
  |  
提交时间:2020/11/14
Cluster analysis
Errors
Iterative methods
Probability distributions
Statistics
Weather forecasting
Wind power
Fitting accuracy
Non-parametric estimations
Segmental clustering
Wind power forecast
Window width
Searching for Hot Subdwarf Stars from the LAMOST Spectra. III. Classification of Hot Subdwarf Stars in the Fourth Data Release of LAMOST Using a Deep Learning Method
期刊论文
ASTROPHYSICAL JOURNAL, 2019, 卷号: 886, 期号: 2, 页码: 10
作者:
Bu, Yude
;
Zeng, Jingjing
;
Lei, Zhenxin
;
Yi, Zhenping
收藏
  |  
浏览/下载:12/0
  |  
提交时间:2020/03/10
methods: data analysis
stars: statistics
subdwarfs
The CFHT large area U-band deep survey (CLAUDS)
期刊论文
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 2019, 卷号: 489, 期号: 4, 页码: 5202-5217
作者:
Sawicki, Marcin
;
Arnouts, Stephane
;
Huang, Jiasheng
;
Coupon, Jean
;
Golob, Anneya
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  |  
浏览/下载:15/0
  |  
提交时间:2020/03/10
galaxies: formation
galaxies: haloes
galaxies: statistics
dark matter
large-scale structure of universe
cosmology: observations
Long rotation period main-sequence stars from Kepler SAP light curves
期刊论文
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 2019, 卷号: 489, 期号: 4, 页码: 5513-5529
作者:
Cui, Kaiming
;
Liu, Jifeng
;
Yang, Shuhong
;
Gao, Qing
;
Yang, Huiqin
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  |  
浏览/下载:18/0
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提交时间:2020/03/10
stars: rotation
stars: starspots
stars: statistics
A loss with mixed penalty for speech enhancement generative adversarial network
会议论文
Lanzhou, China, November 18, 2019 - November 21, 2019
作者:
Cao, Jie
;
Zhou, Yaofeng
;
Yu, Hong
;
Li, Xiaoxu
;
Wang, Dan
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  |  
浏览/下载:1/0
  |  
提交时间:2020/11/15
Speech enhancement
Adversarial networks
First-order statistics
Least Square
Loss functions
Objective and subjective evaluations
Phase mismatch
Speech enhancement methods
Vanishing gradient
Spatial Correlation between Traffic and Air Pollution in Beijing
期刊论文
PROFESSIONAL GEOGRAPHER, 2019, 卷号: 71, 期号: 4, 页码: 654-667
作者:
Jiang, Lili
;
Sun, Ziheng
;
Qi, Qingwen
;
Zhang, An
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2020/05/19
Beijing
geospatial statistics
PM2.5
spatial correlation
traffic-related air pollution
Planetary systems in a star cluster I: the Solar system scenario
期刊论文
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 2019, 卷号: 489, 期号: 2, 页码: 2280-2297
作者:
Dotti, Francesco Flarnrnini
;
Kouwenhove, M. B. N.
;
Cai, Maxwell Xu
;
Spurzem, Rainer
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  |  
浏览/下载:7/0
  |  
提交时间:2020/03/10
planetary systems
stars: solar-type
stars: statistics
galaxy: stellar content
Reconstructing DOA Estimation in the Second-Order Statistic Domain by Exploiting Matrix Completion
期刊论文
Circuits, Systems, and Signal Processing, 2019, 卷号: 38, 期号: 10, 页码: 4855-4873
作者:
Fang, Yunfei
;
Wang, Hongyan
;
Zhu, Shengqi
;
Li, Shaoyong
收藏
  |  
浏览/下载:5/0
  |  
提交时间:2022/02/17
Covariance matrix
Direction of arrival
Vectors
Direction-of-arrival estimators
Elastic regularization
Low signal-to-noise ratio
Matrix completion
Non-uniform
Second order statistics
Sparse reconstruction
Weighted L1 norm
Reconstructing DOA Estimation in the Second-Order Statistic Domain by Exploiting Matrix Completion
期刊论文
CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2019, 卷号: 38, 期号: 10, 页码: 4855-4873
作者:
Fang, Yunfei
;
Wang, Hongyan
;
Zhu, Shengqi
;
Li, Shaoyong
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2019/11/15
Direction of arrival (DOA)
Non-uniform noise
Matrix completion (MC)
Second-order statistics
Weighted l(1) norm
Detection of Outlier of Electric Power Data Based on Improved Fast Density Peak Clustering
会议论文
Chongqing, China, October 11, 2019 - October 13, 2019
作者:
Hao, Xiaohong
;
Li, Hang
;
Zhang, Chunyan
;
Rui, Chen
收藏
  |  
浏览/下载:14/0
  |  
提交时间:2020/11/15
Anomaly detection
Big data
Electric losses
Electric power transmission networks
Information management
Petroleum industry
Power quality
Statistics
Cluster centers
Density clustering
Electric power
In-depth analysis
Local Outlier Factor
Power data
Relative density
Relative distances
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