Evaluates performance of cepstrum analyses in Gaussian noise, suggesting bicepstrum outperforms under certain conditions.
An analytic performance evaluation of the complex cepstrum, power cepstrum, bicepstrum, and power bicepstrum is presented by providing approximate expressions of the bias and variance of the cepstrum parameters due to the presence of Gaussian noise. The approximations are based on the asymptotic properties of bispectrum estimates, and they are valid for moderate signal-to-noise ratios (SNRs). The assumed model consists of a deterministic signal (e.g. multiple echoes) in additive white Gaussian noise and finite length data. The validity of the analytic expressions is verified with Monte Carlo simulations. Performance comparisons between bicepstrum and cepstrum methods suggest that the improved performance of the bicepstrum is a function of SNR, A( omega ), M, and N.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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Petropulu et al. (1990) studied this question.
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