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Neural Spike Sorting Under Nearly 0 dB Signal-to-Noise Ratio Using Nonlinear Energy Operator and Artificial Neural-Network Classifier
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Kyung Hwan | - |
dc.contributor.author | Kim, Sung June | - |
dc.date.accessioned | 2009-09-07T23:19:29Z | - |
dc.date.available | 2009-09-07T23:19:29Z | - |
dc.date.issued | 2000-10 | - |
dc.identifier.citation | IEEE Trans. Biomed. Eng., vol. 47, pp. 1406-1411, Oct. 2000 | en |
dc.identifier.issn | 0018-9294 | - |
dc.identifier.uri | https://hdl.handle.net/10371/8865 | - |
dc.description.abstract | We report a result on neural spike sorting under conditions
where the signal-to-noise ratio is very low. The use of nonlinear energy operator enables the detection of an action potential, even when the SNR is so poor that a typical amplitude thresholding method cannot be applied. The superior detection ability facilitates the collection of a training set under lower SNR than that of the methods which employ simple amplitude thresholding. Thus, the statistical characteristics of the input vectors can be better represented in the neural-network classifier. The trained neural-network classifiers yield the correct classification ratio higher than 90% when the SNR is as low as 1.2 (0.8 dB) when applied to data obtained from extracellular recording from Aplysia abdominal ganglia using a semiconductor microelectrode array. | en |
dc.description.sponsorship | This work was supported
by the Ministry of Health and Welfare, Korea, under Grant HMP-98- E-1-0006. | en |
dc.language.iso | en | - |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en |
dc.subject | neural-network classifier | en |
dc.subject | neural spike sorting | en |
dc.subject | Extracellular recording | en |
dc.subject | nonlinear energy operator | en |
dc.subject | signal-to-noise ratio | en |
dc.title | Neural Spike Sorting Under Nearly 0 dB Signal-to-Noise Ratio Using Nonlinear Energy Operator and Artificial Neural-Network Classifier | en |
dc.type | Article | en |
dc.contributor.AlternativeAuthor | 김경환 | - |
dc.contributor.AlternativeAuthor | 김성준 | - |
dc.identifier.doi | 10.1109/10.871415 | - |
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