scholarly journals Exploring Causal Physical Mechanisms via Non-Gaussian Linear Models and Deep Kernel Learning: Applications for Ferroelectric Domain Structures

ACS Nano ◽  
2021 ◽  
Author(s):  
Yongtao Liu ◽  
Maxim Ziatdinov ◽  
Sergei V. Kalinin
Keyword(s):  
Linear Models ◽  
Ferroelectric Domain ◽  
Kernel Learning ◽  
Physical Mechanisms ◽  
Domain Structures ◽  
Non Gaussian ◽  
Gaussian Linear Models

Ferroelectric domain structures in LiNbO3 single-crystal fibers

1986 ◽  
Vol 78 (1) ◽  
pp. 135-143 ◽  
Author(s):  
Y.S. Luh ◽  
R.S. Feigelson ◽  
M.M. Fejer ◽  
R.L. Byer
Keyword(s):  
Single Crystal ◽  
Ferroelectric Domain ◽  
Domain Structures ◽  
Crystal Fibers

Formation mechanism for ferroelectric domain structures in a LiNbO3 optical superlattice

1996 ◽  
Vol 68 (19) ◽  
pp. 2642-2644 ◽  
Author(s):  
Ya‐lin Lu ◽  
Yan‐qing Lu ◽  
Xiang‐fei Cheng ◽  
Gui‐peng Luo ◽  
Cheng‐cheng Xue ◽  
...  
Keyword(s):  
Formation Mechanism ◽  
Ferroelectric Domain ◽  
Optical Superlattice ◽  
Domain Structures

scholarly journals Sensitivity of the General Linear Model to Assumptions

2020 ◽  
Vol 6 (5) ◽  
pp. 21-25
Keyword(s):  
Linear Model ◽  
Gaussian Noise ◽  
Linear Models ◽  
General Linear Model ◽  
White Gaussian Noise ◽  
General Linear ◽  
Optimal Estimator ◽  
Significant Performance ◽  
Non Gaussian ◽  
Noise Models

Non-Gaussian noise often causes in significant performance abatement for systems which are designed using Gaussian assumption. This report challenges the question of General Linear Model with White Gaussian Noise assumption in order to define the sensitivity of the performance of an optimal estimator. Gaussian noise models provide an important role in many signal processing applications. The Laplacian and Uniform signal are two worthy examples of noise that can be compared to the White Gaussian Noise, though the sensitivity which can be compared with any non-Gaussian. White Gaussian Noise has been considered for General Linear Models and deviation from whiteness would affect on our estimates under different circumstances. Moreover, new assumptions have been considered to generate different type of signals in order to evaluate the sensitivity of the General Linear Model.

Ferroelectric domain structures in strained BiFeO3 ceramics synthesized by spark plasma sintering

2020 ◽  
Vol 159 ◽  
pp. 110044
Author(s):  
Liwei Zhang ◽  
Hua Ke ◽  
Hongjun Zhang ◽  
Huijiadai Luo ◽  
Fangzhe Li ◽  
...  
Keyword(s):  
Spark Plasma Sintering ◽  
Ferroelectric Domain ◽  
Domain Structures ◽  
Plasma Sintering ◽  
Spark Plasma

Light-Assisted Generation of Tailored Ferroelectric Domain Structures

2006 ◽  
Vol 340 (1) ◽  
pp. 63-67 ◽  
Author(s):  
H. A. Eggert ◽  
F. Kalkum ◽  
M. C. Wengler ◽  
U. Heinemeyer ◽  
K. Buse
Keyword(s):  
Ferroelectric Domain ◽  
Domain Structures

scholarly journals A Robust Non-Gaussian Data Assimilation Method for Highly Non-Linear Models

Atmosphere ◽  
2018 ◽  
Vol 9 (4) ◽  
pp. 126 ◽  
Author(s):  
Elias Nino-Ruiz ◽  
Haiyan Cheng ◽  
Rolando Beltran
Keyword(s):  
Data Assimilation ◽  
Linear Models ◽  
Non Linear ◽  
Non Gaussian ◽  
Gaussian Data

Computer simulation of ferroelectric domain structures in epitaxial BiFeO3 thin films

2008 ◽  
Vol 103 (9) ◽  
pp. 094111 ◽  
Author(s):  
J. X. Zhang ◽  
Y. L. Li ◽  
S. Choudhury ◽  
L. Q. Chen ◽  
Y. H. Chu ◽  
...  
Keyword(s):  
Thin Films ◽  
Computer Simulation ◽  
Ferroelectric Domain ◽  
Domain Structures ◽  
Bifeo3 Thin Films
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