How does Sampling affect a Spectrum?

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SUMMARY

This discussion focuses on the effects of sampling on the spectrum of a signal, specifically analyzing the signal s(t)=sin(400πt) + 0.5cos(12000πt) sampled at 10,000Hz, which is below the Nyquist rate. The results show frequency components at ±200Hz and ±4000Hz, deviating from the expected ±6000Hz in the continuous signal. The conversation highlights the concepts of ideal sampling and sample-and-hold techniques, explaining their impact on the frequency domain through Dirac Deltas and sinc functions, respectively. For further understanding, the book "Communication Systems" by Simon Haykin is recommended.

PREREQUISITES
  • Understanding of Nyquist sampling theorem
  • Familiarity with MATLAB for signal processing
  • Knowledge of frequency domain analysis
  • Concept of ideal sampling versus sample-and-hold techniques
NEXT STEPS
  • Study the Nyquist-Shannon sampling theorem in detail
  • Learn about the effects of sampling on signal reconstruction
  • Explore MATLAB functions for frequency domain analysis
  • Read "Communication Systems" by Simon Haykin for a comprehensive overview
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Signal processing engineers, MATLAB users, students studying communication systems, and anyone interested in the effects of sampling on signal spectra.

frenzal_dude
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Hi, I tried sampling <br /> s(t)=sin(400\pi t) + 0.5cos(12000\pi t)<br /> <br /> at 10000Hz (below the Nyquist sampling rate)
in MATLAB and plotted the spectrum, I found that it had frequencies at +-200Hz (same as the continuous signal version) and +- 4000Hz(instead of 6000Hz in the continuous signal).

Just wondering how sampling actually affects the spectrum of the signal, is there a formula or something which can tell you the frequency components based on the sampling rate?

Thanks for your help,
frenzal
 
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Hi frenzal_dude,

Ideal Sampling (Sampling with an infinitesimally small window) is like convolving the signal in frequency domain by a series of Dirac Deltas. So you would just repeat the spectrum with a spacing = sampling frequency throughout the spectrum.

Sample and hold, also known as Zeroth order sampling, on the other hand is like the ideal sampling, but multuplied by a sinc function in the frequency domain, to account for the finite sampling time.

Let me know if you are having any problem with this. You can also take a look at "Communication Systems" by Simon Haykin; it has a very nice introduction to this topic.
 

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