Aliasing (Under Sampling) | Signals and Systems - Electrical Engineering (EE) PDF Download

ALIASING EFFECT OF UNDERSAMPLING

We have seen how by sampling a Band-limited signal at a rate greater than twice the bandwidth of the signal, it is possible to reconstruct the original signal. But what happens if the sampling rate is less than (or equal to) twice the bandwidth of the band-limited signal?

The different translated versions of the original spectrum overlap in the spectrum of the sampled signal. This effect is called aliasing. If we attempt to reconstruct the original signal using a low-pass filter, we might get a signal completely different from the original signal.


Example:-
Let us now also look at very special example, consider a disc rotating with a single radial line marked on the disc. The flashing strobe acts as a sampling system, since it illuminates the disc for extremely brief time intervals at a periodic rate. When the strobe frequency is much higher then the rotational speed of the disc, the speed of rotation of the disc is perceived correctly. When the strobe frequency becomes equal to the rotational frequency, the line appears to be at same position. When the strobe frequency becomes less than twice the rotational frequency, the rotation appears to be at a lower frequency than is actually the case. Furthermore due to phase reversal, the disc will appear rotating in the reverse direction .This phenomenon is known as stroboscopic effect.

Advantages of aliasing : 
1. Can be made to use fs,i.e. carrier frequency for transmission & use Band Filter.
2. We can use frequency of any multiple of fe
3. Also in this case modulation by Ck do not need pulses with average value zero.

 

Conclusion: 


In this lecture you have learnt:

  • Original signal cannot be reconstructed from undersampled signal because higher frequencies are reflected into lower frequencies in the Fourier transform of the undersampled signal .
  • Stroboscopic effect helps in understanding undersampling.
  • Aliasing is not always undesirable . It has some advantages also.
The document Aliasing (Under Sampling) | Signals and Systems - Electrical Engineering (EE) is a part of the Electrical Engineering (EE) Course Signals and Systems.
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FAQs on Aliasing (Under Sampling) - Signals and Systems - Electrical Engineering (EE)

1. What is aliasing in the context of under sampling?
Ans. Aliasing in under sampling refers to the phenomenon where high-frequency signals are misrepresented or distorted as low-frequency signals due to insufficient sampling. This can lead to a loss of information and inaccurate representation of the original signal.
2. How does aliasing occur in under sampling?
Ans. Aliasing occurs in under sampling when the sampling rate is lower than the Nyquist rate, which is twice the highest frequency present in the signal. When the sampling rate is too low, high-frequency components of the signal fold back into the lower frequency range, resulting in aliasing.
3. What are the consequences of aliasing in under sampling?
Ans. The consequences of aliasing in under sampling can include the loss of high-frequency information, distortion of the signal, and the inability to accurately reconstruct the original signal. This can lead to errors in data analysis, misinterpretation of results, and degraded performance in various applications.
4. How can aliasing be prevented in under sampling?
Ans. To prevent aliasing in under sampling, it is important to ensure that the sampling rate is at least twice the highest frequency present in the signal. This can be achieved by applying appropriate anti-aliasing filters before the sampling process to remove any frequencies that are higher than the Nyquist rate.
5. What are some applications where aliasing in under sampling is a concern?
Ans. Aliasing in under sampling is a concern in various applications, including analog-to-digital conversion, audio and video processing, medical imaging, radar systems, and telecommunications. In these fields, accurate representation of high-frequency signals is crucial, and aliasing can introduce errors and distortions that affect the overall performance and reliability of the systems.
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