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长春光学精密机械与物... [1]
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会议论文 [1]
发表日期
2009 [1]
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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.
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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.
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