Howtosignalprocessing
Aliasing is the effect of new frequencies appearing in the sampled signal after reconstruction, that were not present in the original signal. It is caused by too low sample rate for sampling a particular signal or too high frequencies present in the signal for a particular sample rate.
- What is aliasing in sampling?
- What is the aliasing theorem?
- What is aliasing and how it is reduced?
- What is the meaning of aliasing?
What is aliasing in sampling?
Aliasing occurs when an oscilloscope does not sample the signal fast enough to construct an accurate waveform record. The signal frequency is misidentified, and the waveforms displayed on an oscilloscope become indistinguishable. Aliasing is basically a form of undersampling.
What is the aliasing theorem?
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.
What is aliasing and how it is reduced?
Aliasing is characterized by the altering of output compared to the original signal because resampling or interpolation resulted in a lower resolution in images, a slower frame rate in terms of video or a lower wave resolution in audio. Anti-aliasing filters can be used to correct this problem.
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.
