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RE: All sounds, from the screech of nails on a blackboard to a symphony orchestra, are made up of sine waves.

Or whatever set of orthonormal functions as well, as sines & cosines are not the only useful functions for decomposing audio signals.

In signal processing terms, a function of time is a representation of a signal with perfect time resolution, but no frequency information, while the Fourier transform has perfect frequency resolution, but no time information.

The magnitude of the Fourier transform at a point is how much frequency content there is, but location is only given by phase (argument of the Fourier transform at a point), and standing waves are not localized in time – a sine wave continues out to infinity, without decaying.

This limits the usefulness of the Fourier transform for analyzing signals that are localized in time, notably transients, or any signal of finite extent.

As alternatives to the Fourier transform, in time-frequency analysis, one uses time-frequency transforms or time-frequency distributions to represent signals in a form that has some time information and some frequency information – by the uncertainty principle, there is a trade-off between these.

These can be generalizations of the Fourier transform, such as the short-time Fourier transform or fractional Fourier transform, or can use different functions to represent signals, as in wavelet transforms (mostly used in seismic analysis) and chirplet transforms, with the wavelet analog of the (continuous) Fourier transform being the continuous wavelet transform.

Best Regards
Luca


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