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Paper Abstract and Keywords
Presentation 2011-03-08 10:15
Self-organizing hidden markov models
Nobuhiko Yamaguchi (Saga Univ.) NC2010-166
Abstract (in Japanese) (See Japanese page) 
(in English) The self-organizing mixture models (SOMMs) algorithm was proposed as an expectation-maximization (EM) algorithm that yields topology preserving maps of data based on probabilistic mixture models. Compared to self-organizing maps (SOMs), the SOMM algorithm has a clear interpretation:
it maximizes the sum of data log-likelihood and a penalty term that enforces self-organization. The object of this paper is to extend the SOMM algorithm to deal with multivariate time series. The standard SOMM algorithm assumes that the data are independent and identically distributed samples. However, the i.i.d. assumption is clearly inappropriate for time series. In this paper we propose the extension of the SOMM for multivariate time series, which we call self-organizing hidden Markov models (SOHMM), by assuming that the time series
is generated by hidden Markov models (HMMs).
Keyword (in Japanese) (See Japanese page) 
(in English) self-organizing mixture models / visualization / time series / hidden Markov models / / / /  
Reference Info. IEICE Tech. Rep., vol. 110, no. 461, NC2010-166, pp. 229-234, March 2011.
Paper # NC2010-166 
Date of Issue 2011-02-28 (NC) 
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)
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Conference Information
Committee NC MBE  
Conference Date 2011-03-07 - 2011-03-09 
Place (in Japanese) (See Japanese page) 
Place (in English) Tamagawa University 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To NC 
Conference Code 2011-03-NC-MBE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Self-organizing hidden markov models 
Sub Title (in English)  
Keyword(1) self-organizing mixture models  
Keyword(2) visualization  
Keyword(3) time series  
Keyword(4) hidden Markov models  
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1st Author's Name Nobuhiko Yamaguchi  
1st Author's Affiliation Saga University (Saga Univ.)
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Speaker
Date Time 2011-03-08 10:15:00 
Presentation Time 25 
Registration for NC 
Paper # IEICE-NC2010-166 
Volume (vol) IEICE-110 
Number (no) no.461 
Page pp.229-234 
#Pages IEICE-6 
Date of Issue IEICE-NC-2011-02-28 


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