Optimal Detection, Classification, and Superposition Resolution in Neural Waveform Recordings

Isaac N. Bankman; Kenneth O. Johnson; Wolfger Schneider

doi:10.1109/10.238472

Optimal Detection, Classification, and Superposition Resolution in Neural Waveform Recordings

Isaac N. Bankman, Kenneth O. Johnson, Wolfger Schneider

Research output: Contribution to journal › Article › peer-review

83 Scopus citations

Abstract

The effects of noise autocorrelation on neural waveform recognition (detection, classification, and superposition resolution) are investigated in this study using microelectrode recordings from the cortex of a monkey, Optimal waveform recognition is accomplished by passing the data through a whitening filter before matched filtering for detection or template matching for classification and superposition resolution. Template matching without whitening requires about 40% higher signal-to-noise ratio than template matching with whitening for comparable classification and superposition resolution, The comparable difference for detection is 15%.

Original language	English (US)
Pages (from-to)	836-841
Number of pages	6
Journal	IEEE Transactions on Biomedical Engineering
Volume	40
Issue number	8
DOIs	https://doi.org/10.1109/10.238472
State	Published - Aug 1993
Externally published	Yes

ASJC Scopus subject areas

Biomedical Engineering

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10.1109/10.238472

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abstract = "The effects of noise autocorrelation on neural waveform recognition (detection, classification, and superposition resolution) are investigated in this study using microelectrode recordings from the cortex of a monkey, Optimal waveform recognition is accomplished by passing the data through a whitening filter before matched filtering for detection or template matching for classification and superposition resolution. Template matching without whitening requires about 40% higher signal-to-noise ratio than template matching with whitening for comparable classification and superposition resolution, The comparable difference for detection is 15%.",

author = "Bankman, {Isaac N.} and Johnson, {Kenneth O.} and Wolfger Schneider",

year = "1993",

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AB - The effects of noise autocorrelation on neural waveform recognition (detection, classification, and superposition resolution) are investigated in this study using microelectrode recordings from the cortex of a monkey, Optimal waveform recognition is accomplished by passing the data through a whitening filter before matched filtering for detection or template matching for classification and superposition resolution. Template matching without whitening requires about 40% higher signal-to-noise ratio than template matching with whitening for comparable classification and superposition resolution, The comparable difference for detection is 15%.

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Optimal Detection, Classification, and Superposition Resolution in Neural Waveform Recordings

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