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浏览/检索结果: 共6条，第1-6条 帮助 限定条件 内容类型：会议论文     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Reality Sim: A realistic environment for robot simulation platform of humanoid robot (EI CONFERENCE) 会议论文 5th International Conference on Automation, Robotics and Applications, ICARA 2011, December 6, 2011 - December 8, 2011, Wellington, New zealand Fu Y.; Moballegh H.; Rojas R.; Jin L. 收藏  |  浏览/下载：25/0  |  提交时间：2013/03/25 As a virtual training  testing and evaluating environment  simulation platform becomes a significant component in Soccer Robot project. Nevertheless  the simulated environment in a simulation platform usually has a big gap with the realistic world. In order to solve this issue  we demonstrate a more realistic simulation system which is called Reality Sim with numerous real images. By this system  the computer vision code could be easily tested on simulation platform. For this purpose  previously  an image database with a large quantity of images recorded by camera pose is built. Furthermore  if the camera pose of an image is not included in the database  an interpolation algorithm is used to reconstruct a brand-new realistic image of that pose such that a realistic image could be provided on every robot camera pose. Our results show this system effectively simulates a more realistic environment for simulation platform. 2011 IEEE.   Computer simulation research on cognitive mechanism of human vision (EI CONFERENCE) 会议论文 International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2010, March 13, 2010 - March 14, 2010, Changsha, China Ke H.; You W. 收藏  |  浏览/下载：25/0  |  提交时间：2013/03/25 The development of intelligent system which accorded with human cognitive mechanism will exert a profound influence on national defense  economy  education  culture and etc. A computer simulation method according with cognitive mechanism of human vision was proposed on the basis of Structural Decomposition Theory. Many basic shape feature information tables of similar object from different side can determine a kind of object uniquely. System weighted basic shape features in two different information tables by membership degree and then calculated similarity. The identifying object which had the maximum similarity with it in system was what we needed. The system used 83 pictures of 6 kinds of objects with different side for training and testing. The experiment results demonstrated  task of basic shape extraction  object recognition and others can be completed effectively with the method in paper. The method in paper can be a new attempt on computer simulation method according with cognitive mechanism of human vision from cognitive field. 2010 Crown Copyright.   System identification of tracking error and evaluation of tracking performance using BP neural network (EI CONFERENCE) 会议论文 International Symposium on Photoelectronic Detection and Imaging 2009: Advances in Infrared Imaging and Applications, June 17, 2009 - June 19, 2009, Beijing, China Zhang N.; Shen X.-H. 收藏  |  浏览/下载：14/0  |  提交时间：2013/03/25 A novel approach for evaluating the tracking performance of optoelectronic theodolite is proposed. First  an equivalent mathematic model of tracking error is established. Then  the equivalent sine signal is inputted to the equivalent model  and the outputs are sampled. The results of evaluating the tracking performance are obtained based on the statistical calculation of output produced by equivalent model. Equivalent model using the BP (Backprogration) neural network structure is identified. The training method of BP neural network adopts the LM (Levenberg-Marquardt) algorithm for the sake of speeding up training process. The BP neural network is trained and tested by using the training and testing samples gotten from the simulation model of optoelectronic theodolite tracking system under MATLAB/SIMULINK. The estimate errors of equivalent model including average error  maximum error and standard error are 2.5872e-0060  2.8 and 1.9. The results show that the equivalent model identified based on BP neural network meets the needs of evaluating the tracking performance of optoelectronic theodolite. The accurate evaluation of tracking performance is achieved. 2009 SPIE.   Non-stationary vibration signal analysis and fault diagnosis method of aircraft power plant using wavelet network 会议论文 Chinese Control and Decision Conference 2008, CCDC 2008, Yantai, Shandong, China, July 2, 2008 - July 4, 2008 作者:  Zhao, Jianming;  Liu, Jinjun 收藏  |  浏览/下载：4/0  |  提交时间：2017/01/17 Electric fault currents  Aircraft  Curve fitting  Electric power plants  Least squares approximations  Power plants  Signal analysis  Signal processing  Speech recognition  Systems engineering  Telecommunication  Wavelet transforms  Aero engines  Aeroengine  Eigenvectors  Fault diagnosis  Fault diagnosis method  Fault patterns  Feature vectors  Multi-resolution analysis  Network performances  Network structures  Non-stationary  Pattern recognition  Recursive orthogonal least squares algorithm  Self-organizing learning  Self-organizing learning array  Simulation results  Trained network  Training and testing  Vibration signal analysis  Wavelet networks  Wavelet transform   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 ICO20: Illumination, Radiation, and Color Technologies, August 21, 2005 - August 26, 2005, Changchun, China Zhao H.; Li Z.; Wang C.; Sun J.; Zhou F. 收藏  |  浏览/下载：24/0  |  提交时间：2013/03/25 Munsell color system is selected to establish the mutual conversion between RGB and L*a*b* 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 L*a*b* 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   Challenges of using ICT in education 会议论文 Bucharest, Romania 【关键词】, 2017 作者:  VeronikaHomiakova;  Tomá?Kozík;  PeterArras 收藏  |  浏览/下载：0/0  |  提交时间：2019/12/24 Tools  Testing  Electronic  learning  Big  Data  Information  and  communication  technology  Training