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Paper Abstract and Keywords
Presentation 2012-01-19 16:35
Gaussian Processes based Pre-fault detection with multi-resolutional temporal analysis
Shinsaku Ozaki (Wakayama Univ.), Hisae Shibuya, Shunji Maeda (Hitachi, Ltd.), Toshikazu Wada (Wakayama Univ.) PRMU2011-159 MVE2011-68
Abstract (in Japanese) (See Japanese page) 
(in English) We have been proposed a pre-fault detection system based on Gaussian Processes (GP). The advantage of GP based pre-fault detection is that it can estimate not only the estimated output but also the standard deviation of the output. However, the anomaly can sometimes be detected as short-term phenomena and sometimes as long-term tendency. If we simply apply GP to high-dimensional vectors sampled within wide temporal window, the method requires huge number of training samples to keep the sensitivity and the accuracy. This is because GP is an example based non-linear regression method. For solving this problem, we introduce a multi-resolutional analysis along temporal axis that produces multiple signals with different smoothing windows from a single signal. By applying our GP based pre-fault detection method to these multi-scale signals, we can realize a versatile and reliable pre-fault detection system.
Keyword (in Japanese) (See Japanese page) 
(in English) Anomaly detection / Gaussian Processes / Statistical and temporal analysis / / / / /  
Reference Info. IEICE Tech. Rep., vol. 111, no. 379, PRMU2011-159, pp. 109-114, Jan. 2012.
Paper # PRMU2011-159 
Date of Issue 2012-01-12 (PRMU, MVE) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF PRMU2011-159 MVE2011-68

Conference Information
Committee PRMU MVE CQ IPSJ-CVIM  
Conference Date 2012-01-19 - 2012-01-20 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2012-01-PRMU-MVE-CQ-CVIM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Gaussian Processes based Pre-fault detection with multi-resolutional temporal analysis 
Sub Title (in English)  
Keyword(1) Anomaly detection  
Keyword(2) Gaussian Processes  
Keyword(3) Statistical and temporal analysis  
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1st Author's Name Shinsaku Ozaki  
1st Author's Affiliation Wakayama University (Wakayama Univ.)
2nd Author's Name Hisae Shibuya  
2nd Author's Affiliation Hitachi Limited (Hitachi, Ltd.)
3rd Author's Name Shunji Maeda  
3rd Author's Affiliation Hitachi Limited (Hitachi, Ltd.)
4th Author's Name Toshikazu Wada  
4th Author's Affiliation Wakayama University (Wakayama Univ.)
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Speaker Author-1 
Date Time 2012-01-19 16:35:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # PRMU2011-159, MVE2011-68 
Volume (vol) vol.111 
Number (no) no.379(PRMU), no.380(MVE) 
Page pp.109-114 
#Pages 6 
Date of Issue 2012-01-12 (PRMU, MVE) 

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