Reconstruction of derivatives: Error analysis and design criteria

We present a general Fourier-based formalism which provides an accurate prediction of the approximation error, when the derivative of a signal s(t) is continuously reconstructed from uniform point samples or generalized measurements on s. At the heart of the formalism is the frequency error kernel, which can be minimized to design efficient reconstruction schemes which are near optimal in the least-squares sense.

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