The spectral content of normal tracheal and chest wall breath sounds has been calculated using the fast Fourier transform (FFT) (J. Appl. Physiol. 50: 307-314, 1981). Parameter estimation methods, in particular autoregressive (AR) modeling, are alternative techniques for measuring lung sounds. The outcome of AR modeling of 38 complete breaths picked up simultaneously over the chest walls and tracheae of five normal males was evaluated. The sounds were treated as noise, bounded by a quasi-periodic envelope generated by the cyclic action of breathing, thus causing the sounds to become inherently nonstationary. Normalization of the sounds to their corresponding variance envelopes eliminated the nonstationarity, an important requirement for most signal-processing methods. Subsequently, the AR model order was sought using formal criteria. Orders 6-8 were found to be suitable for normal chest wall sounds, whereas tracheal sounds required at least orders 12-16. Using orders 6 and 12, we compared the prominent spectral features of chest wall and tracheal sounds calculated by AR with those found in the spectra calculated by FFT. The polar representation of the AR roots, calculated from the AR coefficients, showed that normal lung sounds from a group of individuals are characterized by a low variability, suggesting that this method may provide an alternative representation of the sounds. The data presented here show that normal lung sounds, when measured in the frequency domain by either FFT or AR modeling, have a characteristic pattern that is independent of the analysis method.