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Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
武汉物理与数学研究所 [2]
半导体研究所 [2]
力学研究所 [1]
长春光学精密机械与物... [1]
地球化学研究所 [1]
兰州化学物理研究所 [1]
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OAI收割 [7]
iSwitch采集 [1]
内容类型
期刊论文 [6]
会议论文 [2]
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2023 [1]
2014 [2]
2013 [1]
2009 [3]
2008 [1]
学科主题
半导体物理 [1]
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In-plane adjustment of atomic positions and layer-dependent friction in 2D materials
期刊论文
OAI收割
Applied Surface Science, 2023, 期号: 620, 页码: 156810
作者:
Minjuan He
;
Yunfeng Wang
;
Wenhao He
;
Yuan Niu
;
Zhibin Lu
  |  
收藏
  |  
浏览/下载:13/0
  |  
提交时间:2024/01/02
First-principles
2D materials
Layer-dependent friction
Atomic displacement
Brain-state dependent uncoupling of BOLD and local field potentials in laminar olfactory bulb
期刊论文
OAI收割
NEUROSCIENCE LETTERS, 2014, 卷号: 580, 页码: 1-6
作者:
Gong, Ling
;
Li, Bo
;
Wu, Ruiqi
;
Li, Anan
;
Xu, Fuqiang
收藏
  |  
浏览/下载:40/0
  |  
提交时间:2015/06/24
Functional MRI
Olfactory bulb
Blood oxygenation level dependent (BOLD)
Local field potentials (LFP)
Layer-dependent
Complex relationship between BOLD-fMRI and electrophysiological signals in different olfactory bulb layers
期刊论文
OAI收割
NEUROIMAGE, 2014, 卷号: 95, 页码: 29-38
作者:
Li, Bo
;
Gong, Ling
;
Wu, Ruiqi
;
Li, Anan
;
Xu, Fuqiang
收藏
  |  
浏览/下载:47/0
  |  
提交时间:2015/06/24
Functional MRI
Olfactory bulb
Blood oxygenation level dependent (BOLD)
Local field potentials (LFP)
Layer-dependent
A new algorithm for frequency-dependent shear-wave splitting parameters extraction
期刊论文
OAI收割
Journal of Geophysics and Engineering, 2013, 卷号: 10, 期号: 5, 页码: 1-8
作者:
Jian-li Zhang
;
Yun Wang
;
Jun Lu
  |  
收藏
  |  
浏览/下载:21/0
  |  
提交时间:2020/12/18
Fracture Detection
frequency-dependent
Frequency-domain
layer Stripping
Observation of the surface circular photogalvanic effect in inn films
期刊论文
iSwitch采集
Solid state communications, 2009, 卷号: 149, 期号: 25-26, 页码: 1004-1007
作者:
Zhang, Z.
;
Zhang, R.
;
Xie, Z. L.
;
Liu, B.
;
Li, M.
收藏
  |  
浏览/下载:26/0
  |  
提交时间:2019/05/12
Inn
Surface charge accumulation layer
Spin-dependent current
Spin splitting
Oscillatory flow at the onset of convection in two-layer Bénard-Marangoni system
会议论文
OAI收割
60th International Astronautical Congress 2009, IAC 2009, Daejeon, Korea, Republic of, October 12, 2009 - October 16, 2009
作者:
Kang Q(康琦)
;
Li LJ(李陆军)
;
Duan L(段俐)
;
Hu WR(胡文瑞)
收藏
  |  
浏览/下载:23/0
  |  
提交时间:2017/07/14
Critical temperature difference
Depth ratio
Marangoni
Marangoni convection
Onset of convection
Oscillatory flows
Particle image velocimetries
Structure change
Time-dependent
Two layer fluid
Two layers
Velocity field
Observation of the surface circular photogalvanic effect in InN films
期刊论文
OAI收割
solid state communications, 2009, 卷号: 149, 期号: 25-26, 页码: 1004-1007
Zhang Z
;
Zhang R
;
Xie ZL
;
Liu B
;
Li M
;
Fu DY
;
Fang HN
;
Xiu XQ
;
Lu H
;
Zheng YD
;
Chen YH
;
Tang CG
;
Wang ZG
收藏
  |  
浏览/下载:166/1
  |  
提交时间:2010/03/08
InN
Surface charge accumulation layer
Spin-dependent current
Spin splitting
A MLP-PNN neural network for CCD image super-resolution in wavelet packet domain (EI CONFERENCE)
会议论文
OAI收割
2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008, October 12, 2008 - October 14, 2008, Dalian, China
Zhao X.
;
Fu D.
;
Zhai L.
收藏
  |  
浏览/下载:68/0
  |  
提交时间:2013/03/25
Image super-resolution methods process an input image sequence of a scene to obtain a still image with increased resolution. Classical approaches to this problem involve complex iterative minimization procedures
typically with high computational costs. In this paper is proposed a novel algorithm for super-resolution that enables a substantial decrease in computer load. First
decompose and reconstruct the image by wavelet packet. Before constructing the image
use neural network in place of other rebuilding method to reconstruct the coefficients in the wavelet packet domain. Second
probabilistic neural network architecture is used to perform a scattered-point interpolation of the image sequence data in the wavelet packet domain. The network kernel function is optimally determined for this problem by a MLP-PNN (Multi Layer Perceptron - Probabilistic Neural Network) trained on synthetic data. Network parameters dependent on the sequence noise level. This super-sampled image is spatially Altered to correct finite pixel size effects
to yield the final high-resolution estimate. This method can decrease the calculation cost and get perfect PSNR. Results are presented
showing the quality of the proposed method. 2008 IEEE.