A Self-structurizing Neural Network for Online Incremental Learning

Osamu Hasegawa; Furao Shen

doi:10.11499/sicep.2004.0_84_2

SICE Annual Conference 2004

DOI https://doi.org/10.11499/sicep.2004.0_84_2

会議情報

主催: The Society of Instrument and Control Engineers

共催: The IEEE Industrial Electronics Society, The IEEE Robotics and Automation Society, The IEEE Control Systems Society, The IEEE Systems, Man and Cybernetics Society, The Instrumentation, Systems, and Automation Society

A Self-structurizing Neural Network for Online Incremental Learning

*Osamu Hasegawa, Furao Shen

著者情報

キーワード: Machine Learning, Neural Network, Pattern Recognition

会議録・要旨集フリー

p. 84

詳細

抄録

An on-line unsupervised learning mechanism is proposed for unlabeled data which is polluted by noises. By using a similarity threshold and local error based insertion criterion, the system is able to grow incrementally and to accommodate input patterns of on-line non-stationary data distribution.

責任著者(Corresponding author)

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