A cepstrum transforms a logarithmic spectrum back to a time-like coordinate. In the real-cepstrum convention for a discrete-time signal with Fourier transform ,The finite-data version uses an inverse discrete Fourier transform of the log-magnitude spectrum. Zeros require suitable assumptions or numerical regularization. Using log power instead of log magnitude changes the scaling, so the convention must be stated.[ref]
Spectral Audio Signal Processing by Julius O. Smith III. Spectral Envelope Extraction, Cepstral Windowing, equation 11.2
The usefulness comes from convolution: if , then the spectra multiply and their log magnitudes add, giving . Multiplicative source-and-filter effects become additive.
For an ideal echo filter , with real , expanding givesOther coefficients vanish. Thus an echo of amplitude delayed by eight samples gives coefficients at and at . Peaks reveal a delay that originally appeared as spectral ripples. The output coordinate is called quefrency. Keeping only its low-quefrency coefficients can smooth a spectral envelope, while retaining high-quefrency structure can expose repetitions.
Quefrency is the independent coordinate of a cepstrum. When a cepstrum is obtained by an inverse Fourier transform of a logarithmic magnitude spectrum expressed as a function of frequency in hertz, its quefrency coordinate has units of time. A repeated pattern across frequency can consequently appear at the corresponding reciprocal spacing on the quefrency axis.[ref]
Spectral Audio Signal Processing by Julius O. Smith III. Spectral Envelope Extraction, Cepstral Windowing, equation 11.2: inverse transform of log spectral magnitude
For an -point discrete Fourier transform with sampling rate , bin spacing is . The inverse-transform coordinate at index has quefrencyWith , index 40 represents . An ideal echo delayed by 40 samples generates spectral ripples spaced by and a cepstrum contribution at that delay, with further contributions at its multiples. The cepstrum's real-valued convention can also produce mirrored peaks at negative quefrencies.
A quefrency peak is therefore not a -period oscillation of the original waveform by definition. Depending on the signal, it might reflect an echo or a fundamental frequency near . Interpretation requires a model of how the spectral repetition arose.
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The cepstrum is a type of signal processing technique used primarily in the analysis of signals, particularly in applications like speech processing, image analysis, and seismic data processing. It is derived from the spectrum of a signal, but it involves manipulating the Fourier transform of that signal. Here’s a more detailed explanation of the concept: ### Definition The cepstrum of a signal is defined as the inverse Fourier transform of the logarithm of the power spectrum of the signal.