Abstract
VSF−Network is a neural network model that learns dynamical patterns. It is hybrid neural network combining a chaos neural network and a hierarchical neural network. The hierarchical neural network learns patterns and the chaos neural network monitors behavior of neurons in the hierarchical neural network. In this paper, two theoretical backgrounds of VSF−Network are introduced. An incremental learning framework using chaos neural networks is introduced. The monitoring by chaos neural network is based on clusters generated by synchronous vibration. Using the monitoring results, redundant neurons in the hierarchical neural network are found and they are used for learning of new patters. The second background is about the pattern recognition by combining learned patterns. This is explained by code words expression used in multi-level discrimination. Through an experiment, both the incremental learning capability and the pattern recognition are shown.
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Kakemoto, Y., Nakasuka, S. (2017). Learning Symbols by Neural Network. In: Angelov, P., Manolopoulos, Y., Iliadis, L., Roy, A., Vellasco, M. (eds) Advances in Big Data. INNS 2016. Advances in Intelligent Systems and Computing, vol 529. Springer, Cham. https://doi.org/10.1007/978-3-319-47898-2_10
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DOI: https://doi.org/10.1007/978-3-319-47898-2_10
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