Signal to Noise Ratio: Definition & Wiener Filter Calculation

In summary, the conversation discusses the concept of signal to noise ratio and how to calculate it using a wiener filter. It is explained that the filter can be used to improve the ratio and the process of calculating the signal to noise ratio improvement is discussed. The use of wiener filter to process a signal with random noise is also mentioned, along with the calculation of the SNR of the interference and the output. The process of applying the filter on the signal and noise to observe the results is also mentioned.
  • #1
cutesteph
63
0
What is signal to noise ratio ? And how do I calculate it with the wiener filter?
 
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  • #2
You need to know how the signal and the noise look like at the filter input and calculate what they will be at the output.
Usually a signal has a narrow spectrum, while the noise has a broad (almost flat) spectrum.
Apply a filter to that and see how much power is in signal and how much is in noise at the output of the filter.
 
  • #3
What are you using the filter to do? Since a wiener filter can be used to improve signal to noise, are you actually trying to calculate the signal to noise ratio improvement by your filter?

Do you understand wiener design? Do you understand this? http://en.wikipedia.org/wiki/Wiener_filter
 
  • #4
I am using it to process a signal say x(n) = sin(nw+theta) +w(n) where w(n) is random noise and say I use a 2 and 3 tap and get wiener values …. [.5 ; -.4] and [-6 ; 15; -5] (note: these are not actual values). I want to calculate the SNR of the interference and SNR of the output. Is the SNR of the output just processing x(n) through each filter i.e. 1/(1-.5z^-1) and then 1/(z-.4z^-1)?
 
  • #5
Yes, apply the filter on the signal (sin(...)) and the noise (w) and see what happens.
 

1. What is the definition of signal to noise ratio?

The signal to noise ratio (SNR) is a measure of the strength of a signal compared to the level of background noise present. It is typically expressed in decibels (dB) and is calculated by dividing the power of the signal by the power of the noise.

2. Why is SNR important in signal processing?

SNR is important because it helps to evaluate the quality of a signal and determine the level of noise present. In many applications, a high SNR is desired in order to minimize the effect of noise on the signal.

3. How is SNR related to the Wiener filter?

The Wiener filter is a signal processing technique used to improve the SNR of a signal by reducing the effects of noise. It does this by taking into account the noise characteristics and using an optimal filter to enhance the signal.

4. How is SNR calculated?

SNR can be calculated in various ways depending on the type of signal and noise present. In general, it can be calculated by dividing the signal power by the noise power, or by comparing the amplitude of the signal to the amplitude of the noise.

5. What is a good SNR value?

A good SNR value can vary depending on the specific application and the type of signal being analyzed. In general, a higher SNR is desired, with values above 20 dB considered to be good for most applications. However, the acceptable SNR may be lower in certain cases, such as in low-power or low-budget systems.

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