Title:
Dynamic Spectral Clustering
Dynamic Spectral Clustering
dc.contributor.author | LaViers, Amy | en_US |
dc.contributor.author | Rahmani, Amir R. | en_US |
dc.contributor.author | Egerstedt, Magnus B. | en_US |
dc.contributor.corporatename | Georgia Institute of Technology. School of Electrical and Computer Engineering | en_US |
dc.contributor.corporatename | Georgia Institute of Technology. Center for Robotics and Intelligent Machines | en_US |
dc.date.accessioned | 2012-02-13T20:46:46Z | |
dc.date.available | 2012-02-13T20:46:46Z | |
dc.date.issued | 2010-07 | |
dc.description | Presented at the 19th International Symposium on Mathematical Theory of Networks and Systems, MTNS 2010, University Congress Center, Budapest, Hungary, July 2010. | en_US |
dc.description.abstract | Clustering is a powerful tool for data classification; however, its application has been limited to analysis of static snapshots of data which may be time-evolving. This work presents a clustering algorithm that employs a fixed time interval and a time-aggregated similarity measure to determine classification. The fixed time interval and a weighting parameter are tuned to the system’s dynamics; otherwise the algorithm proceeds automatically finding the optimal cluster number and appropriate clusters at each time point in the dataset. The viability and contribution of the method is shown through simulation | en_US |
dc.identifier.citation | LaViers, A. Rahmani, and M. Egerstedt, "Dynamic Spectral Clustering," Mathematical Theory of Networks and Systems, Budapest, Hungary, July 2010. | en_US |
dc.identifier.uri | http://hdl.handle.net/1853/42615 | |
dc.language.iso | en_US | en_US |
dc.publisher | Georgia Institute of Technology | en_US |
dc.subject | Clustering | en_US |
dc.subject | Data classification | en_US |
dc.subject | Algorithms | en_US |
dc.subject | Fixed time interval | en_US |
dc.subject | Time-aggregated similarity measure | en_US |
dc.title | Dynamic Spectral Clustering | en_US |
dc.type | Text | |
dc.type.genre | Proceedings | |
dspace.entity.type | Publication | |
local.contributor.author | Egerstedt, Magnus B. | |
local.contributor.corporatename | School of Electrical and Computer Engineering | |
local.contributor.corporatename | College of Engineering | |
relation.isAuthorOfPublication | dd4872d3-2e0d-435d-861d-a61559d2bcb6 | |
relation.isOrgUnitOfPublication | 5b7adef2-447c-4270-b9fc-846bd76f80f2 | |
relation.isOrgUnitOfPublication | 7c022d60-21d5-497c-b552-95e489a06569 |
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