中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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Simulation test research of using the Ritchey-Common method for the detection of large flat mirror (EI CONFERENCE) 会议论文  OAI收割
2012 International Conference on Frontiers of Advanced Materials and Engineering Technology, FAMET 2012, January 4, 2012 - January 5, 2012, Xiamen, China
作者:  
Zhang X.;  Zhang X.;  Zhang X.
收藏  |  浏览/下载:16/0  |  提交时间:2013/03/25
Analysis on the influence of random vibration on MEMS gyro precision and error compensation (EI CONFERENCE) 会议论文  OAI收割
2011 3rd International Conference on Mechanical and Electronics Engineering, ICMEE 2011, September 23, 2011 - September 25, 2011, Hefei, China
作者:  
Li M.
收藏  |  浏览/下载:22/0  |  提交时间:2013/03/25
In order to improve its precision in dynamic environment  a Kalman filter was designed. Firstly  two sets of random drift data of MEMS gyro were respectively analysed  and it was found that the variance of random drift under random vibration significantly increased and its mean also changed. Then calculation results show that attitude angle error under random vibration is 2.6  while in the static test it is 0.25. Analysis on the characteristics of random drift was carried out  and it is found that it can be treated as stable  normally distributed random signal. Finally  a corresponding Kalman filter was designed. The results indicated that after filtering the variance of random drift is reduced to 0.0282  26.4% of pre-filtering and the attitude angle error is reduced to 1.5  57.7% of pre-filtering. The above method can effectively compensate for the attitude angle error of MEMS gyro caused by random vibration. This study can be a reference to the application of low-cost MEMS gyro in aircraft navigation. (2012) Trans Tech Publications  Switzerland.  
Intelligent MRTD testing for thermal imaging system using ANN (EI CONFERENCE) 会议论文  OAI收割
ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China
Sun J.; Ma D.
收藏  |  浏览/下载:26/0  |  提交时间:2013/03/25
The Minimum Resolvable Temperature Difference (MRTD) is the most widely accepted figure for describing the performance of a thermal imaging system. Many models have been proposed to predict it. The MRTD testing is a psychophysical task  for which biases are unavoidable. It requires laboratory conditions such as normal air condition and a constant temperature. It also needs expensive measuring equipments and takes a considerable period of time. Especially when measuring imagers of the same type  the test is time consuming. So an automated and intelligent measurement method should be discussed. This paper adopts the concept of automated MRTD testing using boundary contour system and fuzzy ARTMAP  but uses different methods. It describes an Automated MRTD Testing procedure basing on Back-Propagation Network. Firstly  we use frame grabber to capture the 4-bar target image data. Then according to image gray scale  we segment the image to get 4-bar place and extract feature vector representing the image characteristic and human detection ability. These feature sets  along with known target visibility  are used to train the ANN (Artificial Neural Networks). Actually it is a nonlinear classification (of input dimensions) of the image series using ANN. Our task is to justify if image is resolvable or uncertainty. Then the trained ANN will emulate observer performance in determining MRTD. This method can reduce the uncertainties between observers and long time dependent factors by standardization. This paper will introduce the feature extraction algorithm  demonstrate the feasibility of the whole process and give the accuracy of MRTD measurement.  
Test data sets and evaluation of gene prediction programs on the rice genome 期刊论文  OAI收割
JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, 2005, 卷号: 20, 期号: 4, 页码: 446-453
作者:  
Li, H;  Liu, JS;  Xu, Z;  Jin, J;  Fang, L
  |  收藏  |  浏览/下载:22/0  |  提交时间:2018/07/30