标题:Vergence eye movement with prediction and learning based on dual visual-local feedback
作者:Guo, Yanan ;Ma, Xin ;Song, Rui ;Rong, Xuewen ;Tian, Xincheng ;Tian, Guohui ;Li, Yibin
作者机构:[Guo, Yanan ;Ma, Xin ;Song, Rui ;Rong, Xuewen ;Tian, Xincheng ;Tian, Guohui ;Li, Yibin ] Department of Control Science and Engineering, Shandong Unive 更多
会议名称:2017 Chinese Automation Congress, CAC 2017
会议日期:20 October 2017 through 22 October 2017
来源:Proceedings - 2017 Chinese Automation Congress, CAC 2017
出版年:2017
卷:2017-January
页码:2035-2040
DOI:10.1109/CAC.2017.8243106
关键词:internal model; prediction and learning; vergence eye movement
摘要:Research results in neurophysiology show the predictive nature of vergence eye movement, vergence eye movement can persistently track a moving target which shifts in distance relative to the head. Few models have attempted to consider prediction of target motion in vergence models. Most models only considered static targets, their input are frozen driving signals. In this paper, a model with estimator and predictor to predict and learn current target vergence is proposed. The internal model is designed to record the learned target dynamics and the selector recognizes the final prediction of the target vergence between predictor and the internal model. Then the final prediction of the target vergence is put to a dual visual-local feedback model of vergence eye movement system proposed by Erkelens. Simulation results are included to suggest the effectiveness of proposed model, especially to the continuous moving targets. © 2017 IEEE.
收录类别:EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050354997&doi=10.1109%2fCAC.2017.8243106&partnerID=40&md5=f4408545c908a6b525eacc6f94c8b2a8
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