Abstract
VSF–Network, Vibration Synchronizing Function Network, is a hybrid neural network combining Chaos Neural Network and hierarchical neural network. VSF–Network is designed for symbol learning. VSF–Network finds unknown parts of input data by comparing to stored pattern and it learns unknown patterns using unused part of the network. New patterns are learned incrementally and they are stored as sub-networks . Combinations of patterns are represented as combinations of the sub-networks. In this paper, the two theoretical backgrounds of VSF–Network are introduced. At the first, an incremental learning framework with Chaos Neural Networks is introduced. Next, the pattern recognition with the combined with symbols is introduced. From the viewpoints of9 differential topology and mixture distribution, the combined pattern recognition by VSF-Network is explained. Through an experiment, both the incremental learning capability and the pattern recognition with pattern combination are shown.
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Kakemoto, Y., Nakasuka, S. (2013). Selective Weight Update for Neural Network – Its Backgrounds. In: Yoshida, T., Kou, G., Skowron, A., Cao, J., Hacid, H., Zhong, N. (eds) Active Media Technology. AMT 2013. Lecture Notes in Computer Science, vol 8210. Springer, Cham. https://doi.org/10.1007/978-3-319-02750-0_12
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DOI: https://doi.org/10.1007/978-3-319-02750-0_12
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