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Optimal detection, classification, and superposition resolution in neural waveform recordings

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3 Author(s)
Bankman, I.N. ; Applied Phys. Lab., Johns Hopkins Univ., Laurel, MD, USA ; Johnson, Kenneth O. ; Schneider, W.

The effects of noise autocorrelation on neural waveform recognition (detection, classification, and superposition resolution) are investigated, 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 (SNR) than template matching with whitening for comparable classification and superposition resolution. The comparable difference for detection is 15%.

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Biomedical Engineering, IEEE Transactions on  (Volume:40 ,  Issue: 8 )