QQ客服 官方微博 反馈留言

浏览/检索结果: 共1条，第1-1条 帮助 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 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：12/0  |  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.