Howtosignalprocessing
Aliasing is when a continuous-time sinusoid appears as a discrete-time sinusoid with multiple frequencies. The sampling theorem establishes conditions that prevent aliasing so that a continuous-time signal can be uniquely reconstructed from its samples. The sampling theorem is very important in signal processing.
- How can sampling theorem prevent aliasing?
- How is sampling rate and aliasing related?
- What is aliasing in Nyquist?
- What is the meaning of aliasing?
How can sampling theorem prevent aliasing?
Aliasing is generally avoided by applying low-pass filters or anti-aliasing filters (AAF) to the input signal before sampling and when converting a signal from a higher to a lower sampling rate.
How is sampling rate and aliasing related?
When the sampling rate is not large enough (not larger than 2B Hz), then interference among adjacent bands will occur, and this results in the phenomenon of aliasing. In this case, the original signal cannot be recovered from the sampled signal.
What is aliasing in Nyquist?
When a component of the signal is above the Nyquist, a sampling error occurs that is called aliasing. Aliasing “names” a frequency above Nyquist by an “alias” the same distance below Nyquist. Sinusoidal signal at 1.3 times Nyquist before sampling into pixels.
What is the meaning of aliasing?
noun. ali·as·ing ˈā-lē-ə-siŋ ˈāl-yə- : an error or distortion created in a digital image that usually appears as a jagged outline. We commonly observe aliasing on television.
