Howtosignalprocessing
Aliasing occurs when a signal is sampled at an insufficient rate. Two different signals can become indistinguishable from each other when they are sampled – they are aliases of each other.
- What is aliasing in data sampling?
- What is aliasing and when does it occur?
- What is the meaning of aliasing?
- What is difference between sampling and aliasing?
What is aliasing in data sampling?
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 and when does it occur?
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 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.
What is difference between sampling and aliasing?
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.
