reconstruct_FFT - Upsampling and Interpolation
Updated 13 Jun 2016
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!
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);
Daniel Frisch (2023). reconstruct_FFT - Upsampling and Interpolation (https://www.mathworks.com/matlabcentral/fileexchange/57651-reconstruct_fft-upsampling-and-interpolation), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Platform CompatibilityWindows macOS Linux
- Signal Processing > Signal Processing Toolbox > Digital and Analog Filters > Multirate Signal Processing >
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