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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%.