Signal-processing methods and auditory models for separation of concurrent harmonic sounds are reviewed, and a processing principle is proposed that cancels harmonic interference in the time-domain. The principle is first formulated in signal processing terms as a time-domain comb-filter. The critical issue of fundamental frequency estimation is investigated and an algorithm is proposed. Tested on a restricted database of natural voiced speech, the algorithm successfully found estimates correct within 3% of an octave for 90% of all frames. Next, the principle is formulated in physiological terms. A hypothetical "neural comb filter" is described, based on neural delay lines and inhibitory synapses, and tested using auditory nerve fiber discharge data obtained in response to concurrent vowels [Palmer, A. R. (1990). "The representation of the spectra and fundamental frequencies of steady-state single- and double-vowel sounds in the temporal discharge patterns of guinea pig cochlear-nerve fibers.," J. Acoust. Soc. Am. 88, pp. 1412-1426]. Processing successfully suppresses the correlates of either vowel in the response of fibers that respond to both, allowing the other vowel to be better represented. The filter belongs to the class of "cancellation models" for which predictions can be made concerning the outcome of certain psychoacoustic experiments. These predictions are discussed in relation to recent experimental results obtained elsewhere.