The Spherical Hidden Markov Self Organizing Map for Learning Time Series Data-Reference-Cited by-同舟云学术

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The Spherical Hidden Markov Self Organizing Map for Learning Time Series Data

Published:2012 Issue: Volume: Page:563-570
ISSN:0302-9743
Container-title:Artificial Neural Networks and Machine Learning – ICANN 2012
language:
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Author:

Niina Gen,Dozono Hiroshi

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-33269-2_71.pdf

Reference4 articles.

1. Akuts, T.: Mathematical Models and Algorithms in Bioinformatics. A Series of Algolithm Science, vol. 12. Kyoritsu Shuppan (2007)

2. Nakatsuka, D., Oyabu, M.: Application of Spherical SOM in Clustering. In: Proc. Workshop on Self-Organizing Maps (WSOM 2003), pp. 203–207 (2003)

3. Lecture Notes in Computer Science;N. Yamaguchi,2010

4. Lecture Notes in Computer Science;R. Jaziri,2011

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1. Hidden Markov models on a self-organizing map for anomaly detection in 802.11 wireless networks;Neural Computing and Applications;2021-01-02

2. HMM Training by Using a Self-Organizing Map for Time Series Prediction;Proceedings of the 9th International Conference on Machine Learning and Computing;2017-02-24

3. Causual Analysis of Data Using 2-Layerd Spherical Self-Organizing Map;2015 International Conference on Computational Science and Computational Intelligence (CSCI);2015-12

4. Basic Study on the Classification of Time Series Data Using a Frequency Integrated Spherical Hidden Markov Self Organizing Map;Journal of Advanced Computational Intelligence and Intelligent Informatics;2015-03-20

5. The Data Analysis of Stock Market Using a Frequency Integrated Spherical Hidden Markov Self Organizing Map;Communications in Computer and Information Science;2015

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