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Summary
DescriptionExample of spectral "folding" caused by sampling a real-valued waveform.png
English: When a continuous-time function is sampled, it becomes indistinguishable from other functions (called aliases) that match the same set of samples. In the frequency domain (Fourier transform), the aliases appear as new frequencies that aren't in the original function. In this example, the original frequency content is between 0 and 22050 Hz. The region [22050,44100] contains new content caused by sampling at 44100 samples/sec. The mirror image effect is referred to as "folding".
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This graphic was created by the following Octave script:
pkgloadsignalgraphics_toolkitgnuplot% This did not work% load 'music.mat' % adds variables wavedata and samplerate to the workspace%{music.mat was created by these steps in program Audacity: • Open a stereo mp3 file. • Right-click on the filename, and choose Split Stereo to Mono in the drop-down menu. • Delete one channel. • Highlight a section to be exported. • Choose Export Selected Audio. • Choose Save As Type: Other Uncompressed Files. • Under Options, set Header=MAT5 and Encoding=Signed 16-bit PCM%}%This did work[wavedata,samplerate]=audioread('music.ogg');pwelch(wavedata,hann(512),0.25,512,samplerate,'whole','dB')xlim([0samplerate])gridtitle('Spectral folding, caused by sampling','FontSize',14)xlabel('Frequency (Hz)','FontSize',14)ylabel('Amplitude (dB)','FontSize',14)
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