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Deconvolution of two discrete time signals in frequency domain

version 1.0.0.0 (7.26 MB) by
Compute deconvolution of two discrete time signals in frequency domain to study wave propagation.

Updated 02 Feb 2017

A robust deconvolution function to study wave propagation. Low pass filtering and resampling the input signals to higher sampling rates may help to eliminate noise and improve pick peaking. An example MatLAB routine with actual input signals to replicate the plot shown here is included in zip file.

Cite As

Dr. Erol Kalkan, P.E. (2021). Deconvolution of two discrete time signals in frequency domain (https://www.mathworks.com/matlabcentral/fileexchange/60644-deconvolution-of-two-discrete-time-signals-in-frequency-domain), MATLAB Central File Exchange. Retrieved .

Dr. Erol Kalkan, P.E.

Thanks, Samuel, I agree with you. This is a perfectly working script.

Samuel Nerenberg

Przemyslaw's comment is a bit silly. this just depends on how your input vectors are arranged. Worst case you might have to turn the semicolon into a comma. This is really just laziness on his part.

Jing Yang

The input vector has to be nx1 instead of 1xn, otherwise running the last line shows matrix concatenation error

well-written routine with easy to follow example

Przemyslaw, I don't think your one star is fair. It is a working function, we used many times in our papers. You are basically saying that S should be a vector array instead of two columns.

Przemyslaw Wachulak

matrix concatenation error, should be
S = [Stmp(L/2:L), Stmp(1:L/2-1)];
not S = [Stmp(L/2:L); Stmp(1:L/2-1)];
inside the function.

Przemyslaw Wachulak

Mahmoud Ebrahimkhani

Marin Grubisic

Chao Li

It works.
Extra notes:
data windowing ref
Understanding FFTs and Windowing, Publish Date: Dec 30, 2016, This white paper is part of our Instrument Fundamentals Series.
Tikhonov regularization ref
https://en.wikipedia.org/wiki/Tikhonov_regularization
How to choose regularization parameter (see "L curve")
Hansen, P. C. (1994). Regularization tools: A Matlab package for analysis and solution of discrete ill-posed problems. Numerical algorithms, 6(1), 1-35.

Aleksandar Zhurovski

Wen Van Zhou

MATLAB Release Compatibility
Created with R2014a
Compatible with any release
Platform Compatibility
Windows macOS Linux