1.The Nyquist Shannon Sampling theorem was named after Harry Nyquist, a famous mathematician who worked at Bell Labs and Claude Shannon.
2.The Sampling Theorem states that a signal can be exactly reproduced if it is sampled at a frequency F, where F is greater than twice the maximum frequency in the signal.
3.Each sample value is associated with the instant in time when it was measured. The reciprocal of the sampling interval is the sampling frequency.
4.When the signal is converted back into a continuous time signal, it results in a phenomenon called aliasing.
5.Aliasing is the presence of unwanted components in the reconstructed signal. It occurs because signal frequencies can overlap if the sampling frequency is too low.
6.When a signal is sampled with a sampling frequency below the sample rate then it is known as under-sampling.
7.When a signal is sampled with a sampling frequency significantly higher than twice the bandwidth then it is known as over-sampling.
8.Oversampling helps avoid aliasing, improves resolution and also reduces noise.
9.Since there can be aliasing distortion at the output, to prevent this the analog-to-digital converter contains an anti-aliasing before conversion to the sampled discrete representation.
2.The Sampling Theorem states that a signal can be exactly reproduced if it is sampled at a frequency F, where F is greater than twice the maximum frequency in the signal.
3.Each sample value is associated with the instant in time when it was measured. The reciprocal of the sampling interval is the sampling frequency.
4.When the signal is converted back into a continuous time signal, it results in a phenomenon called aliasing.
5.Aliasing is the presence of unwanted components in the reconstructed signal. It occurs because signal frequencies can overlap if the sampling frequency is too low.
6.When a signal is sampled with a sampling frequency below the sample rate then it is known as under-sampling.
7.When a signal is sampled with a sampling frequency significantly higher than twice the bandwidth then it is known as over-sampling.
8.Oversampling helps avoid aliasing, improves resolution and also reduces noise.
9.Since there can be aliasing distortion at the output, to prevent this the analog-to-digital converter contains an anti-aliasing before conversion to the sampled discrete representation.
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