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Paper Abstract and Keywords
Presentation 2011-05-20 13:30
Connection between Gaussian Processes and Similarity Based Modeling for Anomaly Detection
Shinsaku Ozaki, Toshikazu Wada (Wakayama Univ.), Shunji Maeda, Hisae Shibuya (Hitachi) IE2011-32 PRMU2011-24 MI2011-24
Abstract (in Japanese) (See Japanese page) 
(in English) Anomaly detection can be applied to health monitoring of industrial plants, human medical conditions, vehicle conditions, and so on. A well-known anomaly detection method “Similarity Based Modeling” (SBM) proposed by Stephan W. Wegerich is acknowledged as an effective and essential method in this field. This report first shows that SBM is naturally derived as a special case of “Gaussian Processes” (GP) by regarding the similarity function in SBM as the kernel function in GP, where GP was proposed before the SBM patent. This fact provides us a new interpretation that GP is an example based nonlinear regression method. Based on this interpretation, next we proposed a method for relaxing the scalability problem of GP, that is, a method for reducing the size of gram matrix consisting of pairwise similarities on training samples. This method picks up the reference data for explaining the input data from the training dataset and dynamically construct “reduced” gram matrix. By using this matrix, we can estimate the output without losing the accuracy. The anomaly detection algorithm is applied to practical health monitoring problem of an electric plant with human operation and we confirmed that our algorithm successfully detect the pre-fault events before the actual fault.
Keyword (in Japanese) (See Japanese page) 
(in English) Anomaly detection / Gaussian processes / Statistical and temporal analysis / Similarity Based Modeling / / / /  
Reference Info. IEICE Tech. Rep., vol. 111, no. 48, PRMU2011-24, pp. 133-138, May 2011.
Paper # PRMU2011-24 
Date of Issue 2011-05-12 (IE, PRMU, MI) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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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 IE2011-32 PRMU2011-24 MI2011-24

Conference Information
Committee PRMU MI IE  
Conference Date 2011-05-19 - 2011-05-20 
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 2011-05-PRMU-MI-IE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Connection between Gaussian Processes and Similarity Based Modeling for Anomaly Detection 
Sub Title (in English)  
Keyword(1) Anomaly detection  
Keyword(2) Gaussian processes  
Keyword(3) Statistical and temporal analysis  
Keyword(4) Similarity Based Modeling  
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1st Author's Name Shinsaku Ozaki  
1st Author's Affiliation Wakayama University (Wakayama Univ.)
2nd Author's Name Toshikazu Wada  
2nd Author's Affiliation Wakayama University (Wakayama Univ.)
3rd Author's Name Shunji Maeda  
3rd Author's Affiliation Hitachi, LTD., Yokohama Research Laboratory (Hitachi)
4th Author's Name Hisae Shibuya  
4th Author's Affiliation Hitachi, LTD., Yokohama Research Laboratory (Hitachi)
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Speaker Author-1 
Date Time 2011-05-20 13:30:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # IE2011-32, PRMU2011-24, MI2011-24 
Volume (vol) vol.111 
Number (no) no.47(IE), no.48(PRMU), no.49(MI) 
Page pp.133-138 
#Pages
Date of Issue 2011-05-12 (IE, PRMU, MI) 


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