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在“
Elsevier电子期刊
”中,
命中:
10,042
条,耗时:0.1119447 秒
在所有数据库中总计命中:
111,014
条
1.
Li-ion dynamics and
state
of charge
estimation
作者:
Mingheng Li
minghengli@cpp.edu" class="auth_mail" title="E-mail the corresponding author
关键词:
Li-ion
;
State
of Charge
;
Electrochemical impedance spectroscopy
;
Extended Kalman filtering
;
Joint
state
and parameter
estimation
刊名:Renewable Energy
出版年:2017
2.
On the error
state
selection for stationary SINS alignment and calibration Kalman filters - part I:
Estimation
algorithms
作者:
Felipe O. Silva
a
;
felipe.oliveira@deg.ufla.br
;
Elder M. Hemerly
b
;
hemerly@ita.br
;
Waldemar C. Leite Filho
c
;
waldclf@gmail.com
关键词:
SINS
;
Alignment
;
Calibration
;
Error
state
selection
;
Estimation
刊名:Aerospace Science and Technology
出版年:2017
3.
Recursive
state
estimation
for complex networks with random coupling strength
作者:
Wenling Li
a
;
b
;
c
;
lwlmath@buaa.edu.cn
Author Vitae
;
Yingmin Jia
a
;
b
;
c
;
ymjia@buaa.edu.cn
Author Vitae
;
Junping Du
d
;
junpingdu@126.com
Author Vitae
关键词:
State
estimation
;
Complex networks
;
Extended Kalman filter
;
Random coupling strength
刊名:Neurocomputing
出版年:2017
4.
A concise account of techniques available for shipboard sea
state
estimation
作者:
Ulrik Dam Nielsen
a
;
b
;
udn@mek.dtu.dk
关键词:
Sea
state
estimation
;
Wave buoy analogy
;
Vessel responses
;
Frequency domain
;
Time domain
刊名:Ocean Engineering
出版年:2017
5.
Event-based finite-time
state
estimation
for Markovian jump systems with quantizations and randomly occurring nonlinear perturbations
作者:
Lijuan Zha
a
;
Jian-an Fang
a
;
jafang@dhu.edu.cn
;
Jinliang Liu
b
;
Engang Tian
c
关键词:
Event-triggered scheme
;
Markovian jump systems
;
State
estimation
;
Quantizations
刊名:ISA Transactions
出版年:2017
6.
Non-fragile mixed H
∞
and passive asynchronous
state
estimation
for Markov jump neural networks with randomly occurring uncertainties and sensor nonlinearity
作者:
Shicheng HuoAuthor Vitae
;
Mengshen ChenAuthor Vitae
;
Hao Shen
;
haoshen10@gmail.com
Author Vitae
关键词:
Markov jump neural networks
;
Randomly occurring uncertainties
;
Mixed H&infin
;
and passive asynchronous
state
estimation
;
Sensor nonlinearity
刊名:Neurocomputing
出版年:2017
7.
Efficient sensor placement for
state
estimation
in structural dynamics
作者:
Eric M. Hernandez
eric.hernandez@uvm.edu" class="auth_mail" title="E-mail the corresponding author
关键词:
Kalman filter
;
Sensor placement
;
State
estimation
;
Stress
estimation
;
Structural dynamics
刊名:Mechanical Systems and Signal Processing
出版年:2017
8.
Online
state
of charge
estimation
for the aerial lithium-ion battery packs based on the improved extended Kalman filter method
作者:
Shunli Wang
a
;
wangshunli@swust.edu.cn
;
Carlos Fernandez
b
;
Liping Shang
a
;
Zhanfeng Li
c
;
Jianchao Li
d
关键词:
Aerial lithium-ion battery
;
Improved extended kalman filter
;
State
of charge
;
Optimal prediction
;
Comprehensive
estimation
刊名:Journal of Energy Storage
出版年:2017
9.
Embedded fiber-optic sensing for accurate internal monitoring of cell
state
in advanced battery management systems part 2: Internal cell signals and utility for
state
estimation
作者:
Anurag Ganguli
a
;
Bhaskar Saha
a
;
Ajay Raghavan
a
;
raghavan@parc.com
;
Peter Kiesel
a
;
Kyle Arakaki
a
;
Andreas Schuh
a
;
Julian Schwartz
a
;
Alex Hegyi
a
;
Lars Wilko Sommer
a
;
Alexander Lochbaum
a
;
Saroj Sahu
a
;
Mohamed Alamgir
b
关键词:
Fiber-optic sensors
;
Battery management systems
;
State
-of-charge
;
State
-of-health
;
Lithium-ion
;
Electric vehicle
刊名:Journal of Power Sources
出版年:2017
10.
State
estimation
for discrete-time Markov jump linear systems with time-correlated measurement noise
作者:
Wei Liu
intervalm@163.com
Author Vitae
关键词:
State
estimation
;
Discrete-time
;
Markov jump
;
Linear systems
;
Time-correlated measurement noise
刊名:Automatica
出版年:2017
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