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题名: A LLE-based Approach to Sensor Fault Detection
作者: Zhang W(张伟) ; Li B(李斌) ; Zhou WJ(周维佳)
作者部门: 机器人学研究室
会议名称: International Joint Conference on Neural Networks
会议日期: June 1-8, 2008
会议地点: Hong Kong, China
会议主办者: IEEE
会议录: 2008 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-8
会议录出版者: IEEE
会议录出版地: NEW YORK
出版日期: 2008
页码: 2425-2429
收录类别: CPCI(ISTP) ; EI
ISSN号: 1098-7576
ISBN号: 978-1-4244-1820-6
摘要: Feature extraction has been widely used in sensor fault detection. Commonly used feature extraction methods such as PCA and MDS involve signal process of liner time-invariant systems, which are less effective in dealing with the nonlinear systems. In this paper, we will present that Local Linear Embedding (LLE) concept is adopted to solve the fault detection problems and that certain enhancement have been made to make LLE approach more efficient and robust in the extraction of signal features. Test results are given to demonstrate the effectiveness of the enhanced LLE method.
产权排序: 1
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/8486
Appears in Collections:机器人学研究室_会议论文

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