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长春光学精密机械与物... [7]
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期刊论文 [31]
会议论文 [18]
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Improved Capon Estimator for High-Resolution DOA Estimation and Its Statistical Analysis
期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 8, 页码: 1716-1729
作者:
Weiliang Zuo
;
Jingmin Xin
;
Changnong Liu
;
Nanning Zheng
;
Akira Sano
收藏
  |  
浏览/下载:12/0
  |  
提交时间:2023/07/20
Capon beamformer
direction-of-arrival (DOA) estimation
large-sample mean-squared-error (MSE)
subspace-based methods
uniform linear array
Best (but oft-forgotten) practices: sample size and power calculation for a dietary intervention trial with episodically consumed foods
期刊论文
AMERICAN JOURNAL OF CLINICAL NUTRITION, 2020, 卷号: 112, 期号: 4, 页码: 920-925
作者:
Zhang, Wei
;
Liu, Aiyi
;
Zhang, Zhiwei
;
Nansel, Tonja
;
Halabi, Susan
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2021/01/14
dietary intervention trials
episodic consumption
power
sample size
type I error
OSLNet: Deep Small-Sample Classification with an Orthogonal Softmax Layer
会议论文
作者:
Li, Xiaoxu
;
Chang, Dongliang
;
Ma, Zhanyu
;
Tan, Zheng-Hua
;
Xue, Jing-Hao
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2020/12/18
Benchmarking
Deep neural networks
Large dataset
TestingBenchmark datasets
Discriminative features
Function spaces
Generalization error bounds
Nonlinear layers
Number of class
Rademacher complexity
Small sample datum
OSLNet: Deep Small-Sample Classification with an Orthogonal Softmax Layer
期刊论文
IEEE Transactions on Image Processing, 2020, 卷号: 29, 页码: 6482-6495
作者:
Li, Xiaoxu
;
Chang, Dongliang
;
Ma, Zhanyu
;
Tan, Zheng-Hua
;
Xue, Jing-Hao
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2020/11/14
Benchmarking
Deep neural networks
Large dataset
Testing
Benchmark datasets
Discriminative features
Function spaces
Generalization error bounds
Nonlinear layers
Number of class
Rademacher complexity
Small sample datum
带工程约束且可剔除错误点船体分段点集匹配方法
期刊论文
大连理工大学学报, 2019, 卷号: 59, 页码: 53-62
作者:
管官
;
廖红玲
;
杨蕖
收藏
  |  
浏览/下载:12/0
  |  
提交时间:2019/12/02
hull blocks point set matching error points elimination random sample consensus algorithm engineering constraint weight vector analytic hierarchy process
Expectation-maximisation model for stochastic distribution network planning considering network loss and voltage deviation
期刊论文
IET GENERATION TRANSMISSION & DISTRIBUTION, 2019, 卷号: 13, 期号: 2, 页码: 248-257
作者:
Qi, Baoxia
;
Chen, Jiajia
;
Zhao, Yanlei
;
Jiao, Pihua
收藏
  |  
浏览/下载:57/0
  |  
提交时间:2019/12/11
particle swarm optimisation
power distribution planning
sampling
methods
wind turbines
stochastic processes
investment
simulated
annealing
wind power plants
continuously increasing demand
forecasting error
forecasting approach
mean-variance-skewness based
expectation maximisation model
uncertain wind power
MVSbEM model
network loss
voltage deviation
power factors
different forecasting
wind
wind turbines
sample uncertain wind speed
wind power
penetration
expectation-maximisation model
stochastic distribution
network planning
substations upgrading
Latin hypercube sampling
method
simulated annealing particle swarm optimisation algorithm
stochastic DNP
Controlling the type I error rate in two-stage sequential adaptive designs when testing for average bioequivalence
期刊论文
STATISTICS IN MEDICINE, 2018, 卷号: 37, 期号: 10, 页码: 1587-1607
作者:
Maurer, Willi
;
Jones, Byron
;
Chen, Ying
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2019/08/22
average bioequivalence
type I error control
two-stage design
combination of p-values test
TOST
conditional power
sample size reestimation
A class of model averaging estimators
期刊论文
ECONOMICS LETTERS, 2018, 卷号: 162, 页码: 101-106
作者:
Zhao, Shangwei
;
Ullah, Aman
;
Zhang, Xinyu
收藏
  |  
浏览/下载:16/0
  |  
提交时间:2018/07/30
Finite sample size
Mean squared error
Model averaging
Sufficient condition
Big multi-step wind speed forecasting model based on secondary decomposition, ensemble method and error correction algorithm
期刊论文
Energy Conversion and Management, 2018, 卷号: 156, 页码: 525-541
作者:
Liu, Hui
;
Duan, Zhu
;
Han, Feng-ze
;
Li, Yan-fei*
收藏
  |  
浏览/下载:38/0
  |  
提交时间:2019/12/03
NWP
numerical weather prediction
CS
Cuckoo search
FS
fuzzy system
WRF
weather research and forecasting
KF
Kalman filter
ARIMA
auto-regressive integrated moving average
ARCH
autoregressive conditional heteroskedasticity
ANN
artificial neural networks
SVM
support vector machine
CRO
Coral Reefs optimization algorithm
ELM
extreme learning machine
MFNN
multi-layer feed-forward neural network
SPSA
simultaneous perturbation stochastic approximation
HM
Hammerstein Model
AR
auto-regressive
AdaBoost
adaptive boosting
MLP
multilayer perceptron
DNN-MRT
deep neural network based meta regression and transfer learning
WD
wavelet decomposition
FEEMD
fast ensemble empirical mode decomposition
EMD
empirical mode decomposition
WPD
wavelet packet decomposition
SSA
singular spectrum analysis
BFGS
Broyden–Fletcher–Goldfarb–Shanno Quasi-Newton Back Propagation
LSSVM
least square support vector machine
PSOGSA
partial swarm optimization combined with gravitational search algorithm
FCM
fuzzy C-means
EEMD
ensemble empirical mode decomposition
SampEn
sample entropy
VMD
variational mode decomposition
MAdaBoost
Modified AdaBoost.RT
WF
wavelet filter
MAE
mean absolute error
MAPE
mean absolute percentage error
RMSE
root mean squared error
CWT
continuous wavelet transform
DWT
discrete wavelet transform
LMD
local mean decomposition
ADMM
alternate direction method of multipliers
Big multi-step wind speed forecasting
Wavelet decomposition
Variational mode decomposition
Sample entropy
Modified adaBoost.RT
Wavelet filter
Controlling the type I error rate in two-stage sequential adaptive designs when testing for average bioequivalence
期刊论文
Statistics in medicine, 2018, 卷号: 37, 页码: 1587-1607
作者:
Maurer Willi[1]
;
Jones Byron[2]
;
Chen Ying[3]
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2019/04/24
TOST
average bioequivalence
combination of p-values test
conditional power
sample size reestimation
two-stage design
type I error control
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