Proceedings of the 3rd International Conference on Mechatronics, Robotics and Automation

Spike sorting based on PCA and improved fuzzy c-means

Authors
Yi Yu, Yun Zhao, Han Liu, Bingchao Dong, Zhenxin Li
Corresponding Author
Yi Yu
Available Online April 2015.
DOI
https://doi.org/10.2991/icmra-15.2015.159How to use a DOI?
Keywords
Spike sorting; detection; clustering; PCA; improvement fuzzy c-means
Abstract
Proper classification of spikes from extracellular recordings is essential for the study of neuronal behavior. A lot of algorithms have been presented in the technical literature. Combining with subtractive clustering and fuzzy c-means, we present a new algorithm named improved fuzzy c-means. Compared with fuzzy c-means, the dependence on the initial centers of improved fuzzy c-means is reduced. Not only do the new algorithm improve the accuracy of classification, but also the results of classification are more stable. Three types of classifier were employed in this paper to assess the performance of the spike sorting algorithm. When the noise level rises gradually, the accuracy of k-means of fuzzy c-means decreased quickly.
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Proceedings
3rd International Conference on Mechatronics, Robotics and Automation
Part of series
Advances in Computer Science Research
Publication Date
April 2015
ISBN
978-94-62520-76-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmra-15.2015.159How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yi Yu
AU  - Yun Zhao
AU  - Han Liu
AU  - Bingchao Dong
AU  - Zhenxin Li
PY  - 2015/04
DA  - 2015/04
TI  - Spike sorting based on PCA and improved fuzzy c-means
BT  - 3rd International Conference on Mechatronics, Robotics and Automation
PB  - Atlantis Press
SP  - 818
EP  - 822
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmra-15.2015.159
DO  - https://doi.org/10.2991/icmra-15.2015.159
ID  - Yu2015/04
ER  -