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西安交通大学 [857]
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期刊论文 [592]
会议论文 [263]
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学位论文 [1]
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2019 [21]
2018 [110]
2017 [100]
2016 [114]
2015 [82]
2014 [57]
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Recursive performance ranking of Kalman filter with mismatched noise covariances
期刊论文
IET CONTROL THEORY AND APPLICATIONS, 2019, 卷号: 13, 页码: 459-466
作者:
Shao, Teng
;
Duan, Zhansheng
;
Ge, Quanbo
;
Liu, Huaping
收藏
  |  
浏览/下载:9/0
  |  
提交时间:2019/11/19
TMSE
filter calculated MSE
mismatched noise covariances
recursive estimation
recursive state estimator
FMSE
mathematical programming
recursive performance ranking
semidefinite deviation
mean square error methods
true MSE
state estimation
covariance matrices
unknown noise covariances
Kalman filter
target tracking
mean squared errors
Kalman filters
Iterative learning control for linear continuous-time switched systems with observation noise
期刊论文
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 2019, 卷号: 41, 页码: 1178-1185
作者:
Yang, Xuan
;
Ruan, Xiaoe
收藏
  |  
浏览/下载:8/0
  |  
提交时间:2019/11/19
Lebesgue-p norm
generalized Young inequality
robustness
iterative learning control
switching rules
Convergence
observation noise
Evidence for complete low-frequency vibration band gaps in a thick elastic steel metamaterial plate
期刊论文
MODERN PHYSICS LETTERS B, 2019, 卷号: 33
作者:
Li, Suobin
;
Dou, Yihua
;
Chen, Tianning
;
Wan, Zhiguo
;
Huang, Jingjing
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2019/11/19
noise- and vibration-reduction
vibration band gaps
Elastic metamaterial
steel plates
Statistical quantification of DC power generated by bistable piezoelectric energy harvesters when driven by random excitations
期刊论文
JOURNAL OF SOUND AND VIBRATION, 2019, 卷号: 442, 页码: 770-786
作者:
Zhang, Chunlin
;
Harne, Ryan L.
;
Li, Bing
;
Wang, K. W.
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  |  
浏览/下载:13/0
  |  
提交时间:2019/11/19
White noise excitation
DC output power
Bistable vibration energy harvesters
Standard rectifying electrical circuit
Stochastic averaging
Electrical studies of Barkhausen switching noise in ferroelectric PZT: Critical exponents and temperature dependence
期刊论文
PHYSICAL REVIEW MATERIALS, 2019, 卷号: 3
作者:
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  |  
浏览/下载:7/0
  |  
提交时间:2019/11/19
Periodic averaging method for impulsive stochastic differential equations with Levy noise
期刊论文
APPLIED MATHEMATICS LETTERS, 2019, 卷号: 93, 页码: 91-97
作者:
Ma, Shuo
;
Kang, Yanmei
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  |  
浏览/下载:5/0
  |  
提交时间:2019/11/19
Periodic averaging
Levy noise
Averaging method
Impulsive stochastic differential equations
Maximum Total Correntropy Diffusion Adaptation over Networks with Noisy Links
期刊论文
IEEE Transactions on Circuits and Systems II: Express Briefs, 2019, 卷号: 66, 页码: 307-311
作者:
He, Yicong
;
Wang, Fei
;
Wang, Shiyuan
;
Ren, Pengju
;
Chen, Badong
收藏
  |  
浏览/下载:9/0
  |  
提交时间:2019/11/19
Adaptation models
correntropy
Cost function
distributed estimation
Estimation
Gaussian noise
Noise measurement
robust method.
Robustness
Stability analysis
Multiple Laser Stripe Scanning Profilometry Based on Microelectromechanical Systems Scanning Mirror Projection.
期刊论文
Micromachines, 2019, 卷号: 10
作者:
Hu Gailing
;
Zhou Xiang
;
Zhang Guanliang
;
Zhang Chunwei
;
Li Dong
收藏
  |  
浏览/下载:11/0
  |  
提交时间:2019/11/19
MEMS scanning mirror
MLSSP
vibration noise
laser stripe width
3D measurement
The development of a deep neural network and its application to evaluating the interior sound quality of pure electric vehicles
期刊论文
Mechanical Systems and Signal Processing, 2019, 卷号: 120, 页码: 98-116
作者:
Huang, Hai B.
;
Wu, Jiu H.
;
Huang, Xiao R.
;
Yang, Ming L.
;
Ding, Wei P.
收藏
  |  
浏览/下载:8/0
  |  
提交时间:2019/11/19
Acoustic predictions
Back-propagation neural networks
Interior noise
Laplacians
Psycho-acoustic metrics
Pure electric vehicles
Sound Quality
Subjective evaluations
Particle swarm Optimized Density-based Clustering and Classification: Supervised and unsupervised learning approaches
期刊论文
Swarm and Evolutionary Computation, 2019, 卷号: 44, 页码: 876-896
作者:
Guan, Chun
;
Yuen, Kevin Kam Fung
;
Coenen, Frans
收藏
  |  
浏览/下载:15/0
  |  
提交时间:2019/11/19
Appropriate fitness function
Density-based Clustering
Density-based spatial clustering of applications with noise
Imbalanced dataset
Optimization problems
Parameter-tuning
Pattern recognition technologies
Supervised and unsupervised learning
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