Comprehensive explanation of Aliasing?

In summary, aliasing is a form of distortion that occurs when a continuous signal is digitized. It is caused by sampling a signal at a rate lower than the Nyquist rate, which is the minimum rate required for accurate reconstruction of the original signal. This can be avoided by using a low pass filter before sampling at a rate double the band of the filter.
  • #1
Meriem
8
0
Hello,

I need a comrehensive explanation of Aliasing? and its relation to filters...

Thanks for the answers
 
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  • #2
start with wikipedia...
 
  • #3
http://en.wikipedia.org/wiki/Aliasing

Aliasing is what happens when you take a continuous signal and digitize it. It can only be approximated and as a result, smooth lines in a signal (whether they are a synthesized sound wave or a picture or some other signal is irrelevant) become jagged.
 
  • #4
Aliasing is a form of distortion that happens when you sample a signal with a frequency less than the nyquist rate, the sampling theory simply states that if we take a number of samples of a signal at double the rate of it's highest frequency, the original signal can be reconstructed using these samples, so what happens when you sample at a rate lower than nyquist is that there will be an aliasing effect.

The aliasing effect could be removed by passing the signal through a low pass filter before sampling, thus we could calculate the band of the filter and multiply it by two and then sample at this rate.
 
  • #5
Thanks a lot guys, I have already used wiki...Thanks again!

I will post my summary in the coming days so we all benifit from it!
 

1. What is aliasing?

Aliasing is a phenomenon that occurs when a signal or a function is sampled at a rate that is too low, resulting in an inaccurate representation of the original signal or function.

2. How does aliasing affect data analysis?

Aliasing can lead to errors in data analysis, as it can introduce false frequencies and distort the data. This can result in incorrect conclusions being drawn from the data.

3. What causes aliasing?

Aliasing is caused by the Nyquist-Shannon sampling theorem, which states that in order to accurately represent a signal or function, it must be sampled at a rate at least twice the highest frequency component of the signal.

4. Can aliasing be prevented?

Aliasing can be prevented by properly sampling signals and functions at the proper rate. This can be achieved by using a low-pass filter to remove high frequency components before sampling, or by using a higher sampling rate.

5. How is aliasing addressed in digital signal processing?

In digital signal processing, aliasing is addressed by using techniques such as oversampling, anti-aliasing filters, and signal reconstruction methods to prevent or minimize the effects of aliasing. These techniques help to ensure that the digital representation of the signal is as close to the original analog signal as possible.

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