The spherical hidden markov self organizing map for learning time series data

Authors:
Gen Niina;Hiroshi Dozono
Affiliations:
Faculty of Science and Engineering, Saga University, Saga, Japan;Faculty of Science and Engineering, Saga University, Saga, Japan
Venue:
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part I
Year:
2012

Citing 2
Cited 0

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SOS-HMM: self-organizing structure of hidden Markov model

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Abstract

In modern society, the more complex information and technology become, the more important data analysis become. In particular, a data, which has a variety of elements, is complex, and it is extremely difficult to estimate the state which generates data from observed data. To handle those hidden states, we propose an appropriate model using Spherical-Self Organizing Map (S-SOM) with Hidden Markov Model (HMM) which can estimate the hidden state.