Nyquist Sampling Theorem
Why is the Nyquist sampling theorem important?
The Nyquist theorem is important because it suggests that sampled signals can be accurately reconstructed without loss of information, aliasing or distortion.
What are some practical applications of Nyquist sampling theorem?
Nyquist Sampling theorem is heavily used in Telecommunication, and fields such as audio and image sampling, digital and signal definition.
What is Sampling Interval?
It is referred to as the time interval between the samples taken from a signal during analog to digital conversion, often referred to as ADC . In simple words, it refers to the time interval at which the signal is measured
Nyquist Sampling Theorem
Nyquist Theorem also referred to as the Sampling Theorem is a principle of reproducing a sample rate, that is at least twice the frequency of the original signal. This principle is very important in all analog-to-digital conversion and is applied in digital audio and video to minimize a problem referred to as Aliasing.
In digital communication, signals are representations of information that are transmitted from one point to another in a digital format. Nyquist Sampling is a critical theorem that is used to derive the frequency of the signal to reconstruct without aliasing. Aliasing refers to the distortion or unwanted noise that may destroy a signal’s integral value.