Automatic smoothing and differentiation of a noisy time series
Updated 12 Dec 2017

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This is a code for off-line smoothing and estimation of first and second derivatives of a function from a sequence of noisy measurements, which can be nonequally spaced. The algorithm is automatic: the user does not need to provide smoothing parameters, they are estimated in the code. The signal is modelled as a stationary double-integrated Wiener process and estimates are computed using a Kalman smoother. Theoretical details of the algorithm are presented in

Cite As

Robert Piche (2024). derest (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2017a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes

Added interpolation capability (implemented by Siva Kannan).

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