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by xeonmc
1157 days ago
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> so the fourier transform is just a special case of the laplace transform with σ = 0 Another useful way of looking at it: Laplace transform is doing many extra Fourier-transform-but-with-decay giving you a map of which "global decay timescale" fits your data best -- since each "slice" is itself sufficient to fully describe the time series They are all cases of integral transforms with different choices of the set of "primitive fingerprints" -- see chirp transform, wavelet transform, chirplet transform etc -- all taking advantage of the fact that if you choose one set of basis "brushes" that are not redundant with each other (e.g. having red-green-blue brushes is independent, as is magenta-green-yellow but having red-green-blue-yellow is not) then you will be able to describe your signal in terms of a composition of those kernels. |
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> a map of which "global decay timescale" fits your data best
What do you mean by this?
> -- since each "slice" is itself sufficient to fully describe the time series
But each slice is multiplied by an exponent.. which, okay, becomes a convolution that lets you recover the original function