Nyquist’s Theorem
When reconstructing an analog signal from discrete sample points and Nyquist’s sampling theorem is not valid, what happens to the sampled data?
Expand Hint
Nyquist's (Shannon's) sampling theorem states that in order to accurately reconstruct the analog signal from the discrete sample points, the sample rate must be larger than twice the highest frequency contained in the measured signal.
Hint 2
Also known as alias frequencies.
Nyquist's (Shannon's) sampling theorem states that in order to accurately reconstruct the analog signal from the discrete sample points, the sample rate must be larger than twice the highest frequency contained in the measured signal:
$$$f_s>2f_N$$$
where
$$f_s$$
is the sampling rate or frequency, and
$$f_N$$
is the Nyquist frequency which is the highest frequency contained in a measured signal.
When the sampling theorem is not valid, the higher frequencies from the measured signal will be inaccurately displayed as lower frequencies in the sampled data. These are also known as alias frequencies.
The higher frequencies from the measured signal will be inaccurately displayed as lower frequencies.
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Similar Problems from FE Section: Sampling
139. Shannon Sampling Theorem