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Conference Paper: Signal self organizing map
Title | Signal self organizing map |
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Authors | |
Issue Date | 2007 |
Publisher | Institute of Electrical and Electronics Engineers. The Journals web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000500 |
Citation | The 2007 International Joint Conference on Neural Networks (IJCNN 2007), Orlando, FL., 12-17 August 2007. In IEEE International Conference on Neural Networks Proceedings, 2007, p. 213-218 How to Cite? |
Abstract | The self organizing map (SOM) has been applied to wide ranges of fields including computer vision and image processing. Despite of its simple training algorithm, the vectoral input pattern of SOMs induced a sequence of drawbacks which should not be overlooked. These drawbacks include optimal description length selection problem and inaccurate clustering of scattered point patterns. In this article, an extension of SOM to continuous domain, namely signal SOM (SSOM), is proposed to tackle the drawbacks caused by the vectoral input pattern SOMs. Remarkably, it provides an analytical model expression and involves no model selection problem. The SSOM is evaluated by a simulation about clustering of three signal groups. By comparing with the conventional SOM, a more structural map in term of signal group distribution is obtained by the SSOM. Thus, it indicate the contribution of this article on extending the ability of SOM. ©2007 IEEE. |
Persistent Identifier | http://hdl.handle.net/10722/196697 |
ISBN | |
ISSN |
DC Field | Value | Language |
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dc.contributor.author | Chow, CK | - |
dc.contributor.author | Yuen, SY | - |
dc.date.accessioned | 2014-04-24T02:10:34Z | - |
dc.date.available | 2014-04-24T02:10:34Z | - |
dc.date.issued | 2007 | - |
dc.identifier.citation | The 2007 International Joint Conference on Neural Networks (IJCNN 2007), Orlando, FL., 12-17 August 2007. In IEEE International Conference on Neural Networks Proceedings, 2007, p. 213-218 | - |
dc.identifier.isbn | 978-1-4244-1379-9 | - |
dc.identifier.issn | 1098-7576 | - |
dc.identifier.uri | http://hdl.handle.net/10722/196697 | - |
dc.description.abstract | The self organizing map (SOM) has been applied to wide ranges of fields including computer vision and image processing. Despite of its simple training algorithm, the vectoral input pattern of SOMs induced a sequence of drawbacks which should not be overlooked. These drawbacks include optimal description length selection problem and inaccurate clustering of scattered point patterns. In this article, an extension of SOM to continuous domain, namely signal SOM (SSOM), is proposed to tackle the drawbacks caused by the vectoral input pattern SOMs. Remarkably, it provides an analytical model expression and involves no model selection problem. The SSOM is evaluated by a simulation about clustering of three signal groups. By comparing with the conventional SOM, a more structural map in term of signal group distribution is obtained by the SSOM. Thus, it indicate the contribution of this article on extending the ability of SOM. ©2007 IEEE. | - |
dc.language | eng | - |
dc.publisher | Institute of Electrical and Electronics Engineers. The Journals web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000500 | - |
dc.relation.ispartof | IEEE International Conference on Neural Networks Proceedings | - |
dc.rights | ©2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. | - |
dc.title | Signal self organizing map | - |
dc.type | Conference_Paper | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1109/IJCNN.2007.4370957 | - |
dc.identifier.scopus | eid_2-s2.0-51749091985 | - |
dc.identifier.spage | 213 | - |
dc.identifier.epage | 218 | - |
dc.publisher.place | United States | - |
dc.customcontrol.immutable | sml 160603 amended | - |
dc.identifier.issnl | 1098-7576 | - |