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CAS IR Grid
机构
上海应用物理研究所 [3]
物理研究所 [2]
长春光学精密机械与物... [1]
自动化研究所 [1]
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OAI收割 [7]
内容类型
期刊论文 [5]
会议论文 [1]
学位论文 [1]
发表日期
2019 [1]
2018 [2]
2012 [2]
2011 [2]
学科主题
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Hybridization Effects Revealed by Angle-Resolved Photoemission Spectroscopy in Heavy-Fermion Ce2IrIn8
期刊论文
OAI收割
CHINESE PHYSICS LETTERS, 2019, 卷号: 36, 期号: 9, 页码: -
作者:
Liu, HJ
;
Xu, YJ
;
Zhong, YG
;
Guan, JY
;
Kong, LY
  |  
收藏
  |  
浏览/下载:22/0
  |  
提交时间:2020/10/16
HIDDEN-ORDER
RH
ARPES/STM study of the surface terminations and 5f-electron character in URu2Si2
期刊论文
OAI收割
PHYSICAL REVIEW B, 2018, 卷号: 98, 期号: 11, 页码: -
作者:
Zhang, W
;
Lu, HY
;
Xie, DH
;
Feng, W
;
Tan, SY
  |  
收藏
  |  
浏览/下载:50/0
  |  
提交时间:2019/12/17
ELECTRON SUPERCONDUCTOR URU2SI2
HIDDEN-ORDER TRANSITION
FERMI-SURFACE
KONDO-LATTICE
ITINERANT
SPECTROSCOPY
EXCITATIONS
VALENCE
STATE
Emergent states in heavy-electron materials
期刊论文
OAI收割
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2012, 卷号: 109, 期号: 45, 页码: E3060
Yang, YF
;
Pines, D
收藏
  |  
浏览/下载:95/0
  |  
提交时间:2013/09/17
FERMION SUPERCONDUCTOR
KONDO-LATTICE
HIDDEN-ORDER
URU2SI2
MAGNETISM
CERHIN5
UNI2AL3
CECOIN5
Long range order and two-fluid behavior in heavy electron materials
期刊论文
OAI收割
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2012, 卷号: 109, 期号: 45, 页码: E3067
Shirer, KR
;
Shockley, AC
;
Dioguardi, AP
;
Crocker, J
;
Lin, CH
;
apRoberts-Warren, N
;
Nisson, DM
;
Klavins, P
;
Cooley, JC
;
Yang, YF
;
Curro, NJ
收藏
  |  
浏览/下载:38/0
  |  
提交时间:2013/09/18
QUANTUM PHASE-TRANSITIONS
SUPERCONDUCTOR URU2SI2
KONDO-LATTICE
HIDDEN-ORDER
NMR
CERHIN5
基于boosting思想的列表排序算法研究
学位论文
OAI收割
工程硕士, 中国科学院自动化研究所: 中国科学院研究生院, 2011
王永庆
收藏
  |  
浏览/下载:51/0
  |  
提交时间:2015/09/02
排序学习
列表排序方法
boosting
隐序
FeatureRank
BL-FeatureRank
DiffRank
leanring to rank
listwise approach
boosting
hidden order
FeatureRank
BL-FeatureRank
DiffRank
Research on the identification for a nonlinear system (EI CONFERENCE)
会议论文
OAI收割
International Conference on Optical, Electronic Materials and Applications 2011, OEMA 2011, March 4, 2011 - March 6, 2011, Chongqing, China
作者:
Liu J.
;
Jia P.
;
Liu J.
;
Liu J.
收藏
  |  
浏览/下载:32/0
  |  
提交时间:2013/03/25
The characteristic of the drift error of inertial platform is a high-order nonlinear dynamic system
using the neural networks' abilities of universal approximation of differentiable trajectory and capturing system dynamic information
this paper presents the drift error identifying project of inertial platform based on Elman networks structure. First
the drift error model of inertial platform is established
after selecting the input and output for network
momentum and alterable speed algorithm is used to speed up the network convergence. On the basis of the algorithm
the extended nonlinear node function in the hidden network does not only improve the learning speed of network
but also satisfies the need of accuracy on system identification. Through the drift error data measured on inertial platform
the training result shows that the scheme achieves satisfied identification results. (2011) Trans Tech Publications.