Spectral Derivatives (2506.06210v2)

Published 6 Jun 2025 in eess.SP and math.HO

Abstract: One of the happiest accidents in all math is the ease of transforming a function to and taking derivatives in the Fourier frequency domain. But in order to exploit this extraordinary fact without serious artefacting, and in order to be able to use a computer, we need quite a bit of extra knowledge and care. This document sets out the math behind the spectral-derivatives Python package. I touch on fundamental signal processing and calculus concepts as necessary and build upwards.

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Authors (1)

Pavel Komarov

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