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	Function-on-function quadratic regression models 期刊论文 OAI收割 COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2020, 卷号: 142, 页码: 14 作者: Sun, Yifan; Wang, Qihua \| 收藏 \| 浏览/下载：28/0 \| 提交时间：2020/05/24 Functional data analysis Quadratic regression Functional principal component analysis Test of significance Asymptotics
	In-orbit Demonstration of X-Ray Pulsar Navigation with the Insight-HXMT Satellite 期刊论文 OAI收割 The Astrophysical Journal Supplement Series, 2019, 卷号: 244, 页码: 1 作者: HXMT \| 收藏 \| 浏览/下载：15/0 \| 提交时间：2022/02/08 pulsars: general techniques: miscellaneous Astrophysics - Instrumentation and Methods for Astrophysics Abstract: In this work, we report the in-orbit demonstration of X-ray pulsar navigation with Insight-Hard X-ray Modulation Telescope (Insight-HXMT) Satellite, which was launched on 2017 June 15. The new pulsar navigation method Significance Enhancement of Pulse-profile with Orbit-dynamics is adopted to determine the orbit with observations of only one pulsar. In this test, the Crab pulsar is chosen and observed by Insight-HXMT from 2017 August 31 to September 5. Using the five-day long observation data, the orbit of Insight-HXMT is determined successfully with the three telescopes onboard: High Energy X-ray Telescope, Medium Energy X-ray Telescope, and Low Energy X-ray Telescope, respectively. By combining all the data, the position and velocity of the Insight-HXMT are pinpointed to within 10 km (3ҩ and 10 m s^-1 (3ҩ, respectively.
	Evaluation Methods for Discrimination of Metabonomic Data 期刊论文 OAI收割 CHINESE JOURNAL OF ANALYTICAL CHEMISTRY, 2013, 卷号: 41, 期号: 7, 页码: 1000-1005 作者: Zhu Hang; Lan Wen-xian; Liu Mai-Li 收藏 \| 浏览/下载：35/0 \| 提交时间：2015/06/23 Metabonomics Pattern recognition Multivariate statistical analysis Significance test Distance between classes Sum of squares of deviations Nuclear magnetic resonance
	Design and optimization of supporting structure for scanning mirror in aviation remote sensor (EI CONFERENCE) 会议论文 OAI收割 2011 International Conference on Electric Information and Control Engineering, ICEICE 2011, April 15, 2011 - April 17, 2011, Wuhan, China 作者: Yang H. 收藏 \| 浏览/下载：30/0 \| 提交时间：2013/03/25 An optical supporting structure is studied to improve its structure stiffness and reduce the rotate error to meet the requirement of aviation remote sensor. A formula to calculate fundamental frequency is proposed using Rayleigh-Ritz method and a method of is analyzed. By means of OPTISTRUCT software the maximum fundamental frequency is converted to object function the deformation under the gravity and the mass are assigned to state variable wall thicknesses of the structure are converted to design variables. The analysis and test results indicate that the fundamental frequency of designed optical supporting structure has been improved 37.2 Hz from 96.9 Hz which guarantee the reliability of the sweep mechanism and the rotate error is 4.89 which is satisfied for the rotate accuracy in plunge angle. The method of optimization has a certain instructional significance for the design of supporting structures in aviation remote sensor. 2011 IEEE.
	The research on test scheme of the digital Electromechanical Actuator based on CAN Bus (EI CONFERENCE) 会议论文 OAI收割 2011 2nd International Conference on Mechanic Automation and Control Engineering, MACE 2011, July 15, 2011 - July 17, 2011, Inner Mongolia, China 作者: Zhang J.; Zhang J.; Zhang Y.; Zhang J. 收藏 \| 浏览/下载：33/0 \| 提交时间：2013/03/25 In order to realize the digital of Electromechanical Actuator(EMA) control system the CAN Bus which has efficient reliable performance and flexible network modes works as data interface.The EMA test scheme is designed based on the CAN Bus.First of all the microcontroller DSP with the CAN Bus works as the core of the EMA control system circuit boards.Then the CAN Bus test network is established with the EMA Ground Test System and Autopilot computer.The function and self-check of the EMA canbe conveniently tested by the network and the result of the test canbe easily displayed in the PC.Finally the CAN Bus test network is established with the EMA the Frequency Characteristics Scanner and etc.The purpose is to test the performance of the EMA.The result of the test can be intuitively showed on the Frequency Characteristics Scanner.In a word the application of the CAN bus provides a new method to test the EMA and reference to engineering the digital EMA which has vital significance. 2011 IEEE.
	Study on color model conversion for camera with neural network based on the combination between second general revolving combination design and genetic algorithm (EI CONFERENCE) 会议论文 OAI收割 ICO20: Illumination, Radiation, and Color Technologies, August 21, 2005 - August 26, 2005, Changchun, China 作者: Li Z.; Zhou F.; Wang C.; Li Z. 收藏 \| 浏览/下载：36/0 \| 提交时间：2013/03/25 Munsell color system is selected to establish the mutual conversion between RGB and Lab* color model for camera. The color luminance meter and CCD camera synchronously measure the same color card XYZ value is gotten from the color luminance meter the training error is 0.000748566 it can show that the method combining second general revolving combination design with genetic algorithm can optimize the hidden-layer structure of neural network. Using the data of testing set to test this network and calculating the color difference between forecast value and true value the color picture captured from CCD camera is expressed for RGB value as the input of neural network and the Lab* value converted from XYZ value is regarded as the real color value of target card which the difference is not obvious comparing with forecast result the maximum is 5.6357 NBS namely the output of neural network. The neural network of two hidden-layers is considered the minimum is 0.5311 NBS so the second general revolving combination design is introduced into optimizing the structure of neural network and the average of color difference is 3.1744 NBS. which can carry optimization through unifying project design data processing and the precision of regression equation. Their mathematics model of encoding space is gained and the significance inspection shows the confidence degree of regression equation is 99%. The mathematics model is optimized by genetic algorithm optimization solution is gotten and function value of the goal is 0.0007168. The neural network of the optimization solution is trained