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知网期刊论文(7662)
在“
Elsevier电子期刊
”中,
命中:
2,806
条,耗时:0.1309353 秒
在所有数据库中总计命中:
16,354
条
1.
Generalized entropy based possibilistic fuzzy C-Means for clustering
noisy
data
and its convergence proof
作者:
S. Askari
a
Author Vitae
;
N. Montazerin
a
;
mntzrn@aut.ac.ir
;
mntzrn@hotmail.com
Author Vitae
;
M.H. Fazel Zarandi
b
Author Vitae
;
E. Hakimi
c
Author Vitae
关键词:
Fuzzy C-Means
;
Possibilistic C-Means
;
Entropy C-Means
;
Noise
;
Noisy
data
;
Fuzzy clustering
;
Convergence proof
刊名:Neurocomputing
出版年:2017
2.
Prediction measurement with mean acceptable error for proper inconsistency in
noisy
weldability prediction
data
作者:
Kyoung-Yun Kim
a
;
kykim@eng.wayne.edu" class="auth_mail" title="E-mail the corresponding author
;
Junheung Park
a
;
junheung@wayne.edu" class="auth_mail" title="E-mail the corresponding author
;
Raj Sohmshetty
b
;
rsoshmshe@ford.com" class="auth_mail" title="E-mail the corresponding author
关键词:
Weldability prediction
;
Data
inconsistency
;
Proper inconsistency
;
Mean acceptable error
;
Prediction measurement
刊名:Robotics and Computer-Integrated Manufacturing
出版年:2017
3.
Reconstruction of 3D scattered
data
via radial basis functions by efficient and robust techniques
作者:
Alberto Crivellaro
a
;
Simona Perotto
b
;
Stefano Zonca
b
;
stefano.zonca@polimi.it
关键词:
Multivariate interpolation
;
Least-squares approximation
;
Adaptive algorithm
;
Radial basis functions
;
3D
noisy
and lacking scattered
data
刊名:Applied Numerical Mathematics
出版年:2017
4.
Robust kernel adaptive filters based on mean p-power error for
noisy
chaotic time series prediction
作者:
Wentao Ma
a
;
mwt7980@aliyun.com
;
Jiandong Duan
a
;
Weishi Man
a
;
Haiquan Zhao
b
;
Badong Chen
c
关键词:
Kernel trick
;
Mean p-power error criterion
;
Noisy
chaotic time series prediction
;
Impulsive noises
刊名:Engineering Applications of Artificial Intelligence
出版年:2017
5.
Screening dense and
noisy
DOX-
data
sets with NN-blending and “dizzy” swarm intelligence: Profiling a water quality process
作者:
George J. Besseris
a
;
b
;
besseris@teipir.gr
关键词:
Stochastic optimization
;
Taguchi methods
;
Swarm intelligence
;
GRNN
;
Smart sampling
;
Water quality
刊名:Swarm and Evolutionary Computation
出版年:2017
6.
Prostate cancer recognition based on mass spectrometry sensing
data
and
data
fingerprint recovery
作者:
Khalfalla Awedat
a
;
awedatka@plu.edu
;
Ikhlas Abdel-Qader
b
;
abdelqader@wmich.edu
;
James R. Springstead
c
;
james.springstead@wmich.edu
关键词:
Compressive sensing
;
Mass spectrometry
;
BSBL
;
MS-classification
;
Confusion matrix
刊名:Biomedical Signal Processing and Control
出版年:2017
7.
Optimal smoothing for spherical Gauss-Markov Random Fields with application to weather
data
estimation
作者:
Alessandro Borri
a
;
alessandro.borri@biomatematica.it
;
Francesco Carravetta
b
;
francesco.carravetta@iasi.cnr.it
;
Langford B. White
c
;
Lang.White@adelaide.edu.au
关键词:
Random fields
;
Estimation and filtering
;
Optimal smoothing
;
Weather
data
;
Geophysical signal processing
刊名:European Journal of Control
出版年:2017
8.
Can we use PCA to detect small signals in
noisy
data
?
作者:
Jakob Spiegelberg
;
Já
;
n Rusz
关键词:
PCA
;
Nullspace based denoising
;
Blind source separation
;
Bias estimation
;
Spectrum imaging
刊名:Ultramicroscopy
出版年:2017
9.
Controlling the equilibria of nonlinear stochastic systems based on
noisy
data
作者:
Irina Bashkirtseva
a
;
irina.bashkirtseva@urfu.ru
;
Lev Ryashko
a
;
lev.ryashko@urfu.ru
;
Guanrong Chen
b
;
eegchen@cityu.edu.hk
刊名:Journal of the Franklin Institute
出版年:2017
10.
The PhysIO Toolbox for Modeling Physiological Noise in fMRI
Data
作者:
Lars Kasper
a
;
b
;
kasper@biomed.ee.ethz.ch
;
Steffen Bollmann
c
;
Andreea O. Diaconescu
a
;
Chloe Hutton
d
;
Jakob Heinzle
a
;
Sandra Iglesias
a
;
Tobias U. Hauser
d
;
e
;
Miriam Sebold
f
;
Zina-Mary Manjaly
g
;
Klaas P. Pruessmann
b
;
Klaas E. Stephan
a
;
d
;
h
关键词:
Physiological noise correction
;
fMRI
;
RETROICOR
;
RVHRCOR
;
Heart rate
;
Respiratory volume
;
SPM toolbox
;
fMRI preprocessing
刊名:Journal of Neuroscience Methods
出版年:2017
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