Affiliation of Author(s):自动化学院
Journal:JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION
Key Words:Robustness Adaptive function Observer
Abstract:A large mount of data is indispensable in deep learning. The learning results can be different because of the noise or contaminate tags. So in this paper, a controller design method is proposed to reduce the influence due to noise or damaged label. Our method is based on backstepping control method and observer. In our work, an adaptive function is designed to eliminate the influence of the unmodelable part of the system because of the contaminated tags. For the noise, the observer is used to accurately estimated and effectively compensated. Experimental results show the effectiveness of our method. Our modified system has good performance and can accurately response the input training data in the case of the unmodelable part of the system and the external noise. (C) 2018 Elsevier Inc. All rights reserved.
ISSN No.:1047-3203
Translation or Not:no
Date of Publication:2018-11-01
Co-author:Li JiGuang
Correspondence Author:TingZhao
Date of Publication:2018-11-01