Abstract
A hybrid approach combining the Self-Organizing Map (SOM) and the Hidden Markov Model (HMM) is presented. The fusion and synergy of the SOM unsupervised training and the HMM dynamic programming algorithms bring forth a scaled on-line gradient descent unsupervised learning algorithm.
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© 2011 Springer-Verlag London Limited
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Ferles, C., Siolas, G., Stafylopatis, A. (2011). Scaled On-line Unsupervised Learning Algorithm for a SOM-HMM Hybrid. In: Gelenbe, E., Lent, R., Sakellari, G. (eds) Computer and Information Sciences II. Springer, London. https://doi.org/10.1007/978-1-4471-2155-8_68
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DOI: https://doi.org/10.1007/978-1-4471-2155-8_68
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Online ISBN: 978-1-4471-2155-8
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