reconstruct_FFT - Upsampling and Interpolation

reconstruct_FFT fills in zeros and performs an ideal lowpass filtering at the nyquist frequency.


Updated 13 Jun 2016

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Reconstruction of Original Signal based on Samples.
Upsampling including ideal lowpass filtering by FFT.
For ideal reconstruction, measurement interval must be
an integral multiple of periodicity of input signal!
Input arguments
1. Time vector (equally spaced)
2. Sample vector (same length as time vector)
Optional Name-Value pairs
- 'Factor', N [positive integer] (default: 100)
Output will have N time as much samples as input.
- 'Plot', [logical] (default: false)
Plots spectrum of intermediate signals.
Or call reconstruct_FFT() without any arguments to view an example.

F_s = 5; % Sampling frequency
f0 = 2; % Signal frequency
time = 0:1/F_s:2-1e-12; % Time vector
samples = cos(2*pi*f0*time); % Signal vector
[ time_rec, samples_rec ] = reconstruct_FFT( time,samples );
figure; stem(time,samples); hold on; plot(time_rec, samples_rec);

Cite As

Daniel Frisch (2023). reconstruct_FFT - Upsampling and Interpolation (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2016a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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