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What is the Nyquist rule of sampling?

Nyquists theorem states that a periodic signal must be sampled at more than twice the highest frequency component of the signal. In practice, because of the finite time available, a sample rate somewhat higher than this is necessary.

What happens if you sample below the Nyquist rate?

When the sampling frequency drops below the Nyquist rate, the frequencies will crossover and cause aliasing.

What are the errors in the sampling theorem?

The most common sampling errors are: round-off of f(nT), truncation of the series generating f(t), aliasing of frequency components above half the sampling rate 1/T, jitter in the recording times nT, loss of a number of sampled values, and imperfect filtering in the recovery of f(t).

How do you find the sampling error?

As per the formula, sampling error is calculated by dividing the populations standard deviation by the square root of the sample size and then multiplying the resultant with the Z-score value based on the confidence interval.

What happens if Nyquist criteria is not followed?

If the Nyquist theorem is not obeyed, higher frequency information is recorded in too low a sample rate, resulting in aliasing artifacts.

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What is the aliasing error in the sampling theorem?

What is the aliasing effect? The aliasing effect is a measurement error in the signal occurring due to an incorrectly set sampling rate. If the sampling rate is too low, the Nyquist-Shannon sampling theorem is not observed and thus the measurement signal is not acquired correctly.

What are the types of sampling errors?

In general, sampling errors can be placed into four categories: population-specific error, selection error, sample frame error, or non-response error.

What are the three conditions of sampling theorem?

If the sampling frequency (Fs) is less than twice the input signal frequency, such criteria called an Aliasing effect. So, there are three conditions that are possible from the sampling frequency criteria. They are sampling, Nyquist and aliasing states. Now we will see the Nyquist sampling theorem.

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