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A robust energy artificial neuron based incremental self-organizing neural network with a dynamic structure
| Title: | A robust energy artificial neuron based incremental self-organizing neural network with a dynamic structure |
| Authors: | Liu, Hao Browse this author | | Sato, Haruhiko Browse this author →KAKEN DB | | Oyama, Satoshi Browse this author →KAKEN DB | | Kurihara, Masahito Browse this author →KAKEN DB |
| Keywords: | self-organizing | | unsupervised learning | | neural network | | incremental learning | | SOM | | REISOD |
| Issue Date: | 2012 |
| Publisher: | IEEE (Institute of Electrical and Electronics Engineers) |
| Citation: | Proceedings 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), ISBN: 978-1-4673-1714-6 |
| Start Page: | 1806 |
| End Page: | 1811 |
| Publisher DOI: | 10.1109/ICSMC.2012.6378000 |
| Abstract: | Self-organizing neural network which is an unsupervised learning algorithm is to discover the inherent relationships of data. Such technique has become an important tool for data mining, machine learning and pattern recognition. Most self-organizing neural networks have a difficulty in reflecting data distributions precisely if data distributions are very complex. And meanwhile, it is also hard for these algorithms to learn new data incrementally without destroying the previous learnt data. In this paper, we propose a robust energy artificial neuron based incremental self-organizing neural network with a dynamic structure (REISOD). It can adjust the scale of network automatically to adapt the scale of the data set and learn new data incrementally with preserving the former learnt results. Moreover, several experiments show that our algorithm can reflect data distributions precisely. |
| Conference Name: | IEEE International Conference on Systems, Man, and Cybernetics (SMC) |
| Conference Sequence: | 2012 |
| Conference Place: | Seoul |
| Rights: | © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| Type: | proceedings (author version) |
| URI: | http://hdl.handle.net/2115/65595 |
| Appears in Collections: | 情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: 小山 聡
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