A multistage mathematical approach to automated clustering of high-dimensional noisy data
A critical problem faced in many scientific fields is the adequate separation of data derived from individual sources. Often, such datasets require analysis of multiple features in a highly multidimensional space, with overlap of features and sources. The datasets generated by simultaneous recording...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
National Academy of Sciences (U.S.)
2015
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| Online Access: | http://hdl.handle.net/1721.1/99117 https://orcid.org/0000-0002-4326-7720 |