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Results tagged with noise
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user 923
In signal processing noise can be considered random unwanted data without meaning.
2
votes
SQNR when multiplying 2 16 bit signed integers and truncating result?
The truncation noise, therefore, is $1.43E9$. … You then calculate the SQNR by dividing the signal power by the truncation noise, $1.43E9$. …
- 12.2k
1
vote
why Gaussian noise is usually used?
How can researchers guarantee that Gaussian noise can simulate the reality of a System?
They cannot guarantee that it is an accurate reflection of all systems. … So why do we use gaussian noise? Two reasons. First, because it does accurately reflect many systems. …
- 12.2k
6
votes
Accepted
PSK vs FSK for noise immunity?
As you say in your comment, PSK signals are more bandwidth efficient, but FSK signals have good noise rejection for their data rates. It is thus difficult to compare them on even terms. … The traditional way of measuring noise immunity is measuring/calculating the probability of a bit error given the bit energy vs. noise energy (Eb/No). …
- 12.2k
1
vote
what does "fixed multipath channel model" means?
Your "h" is a valid multipath channel impulse response. It is a special case, though, in that it represents a multipath delay that is an exact multiple of your sample period. Usually the delay will …
- 12.2k
1
vote
What is the unit of SNR?
SNR is unitless, because when you divide the signal by the noise they have the same units, thus canceling the units out. …
- 12.2k
7
votes
Accepted
How to find quantization noise in my simulation?
The quantization error is the quantization noise. It is two different terms for the same thing. …
- 12.2k
4
votes
Accepted
Questions on the generation of R.O.C. curves
I generate data, scramble it, modulate it, add noise and carrier offset, etc., then I give it to the receiver. The bits I started out with are my "yes/no" labels. … Noise is statistical. Jitter is statistical. A priori channel conditions are statistical. Of course the ROC curve is also statistical. How could it be otherwise? …
- 12.2k
1
vote
How do I numerically calculate a function from its noisy gradient?
At that point you could design a low-pass filter that would preserve the signal but get rid of higher frequency noise. …
- 12.2k
2
votes
Accepted
determining FEC or parity bits from percent error
Is it possible to know with say a reed-Solomon technique how many paity bits I would need to add to each block to move in the neighborhoos of 100%?
Normally yes, if you know that you will never h …
- 12.2k
5
votes
White noise vs. delta pulse and Ultraviolet catastrofe
As Jason was saying in the comments, the power spectral density of white noise is flat. … the noise itself is a delta dirac function. …
- 12.2k
1
vote
Is it possible that adding noise to a signal can increase detection possibility?
If white noise is added to the tone such that the total power of the tone and noise exceeds the threshold, then the ear can hear the tone. …
- 12.2k
5
votes
What do colored noises look like in the time domain?
White noise implies no correlation between samples of the noise, even consecutive samples. … Colored noise, therefore, implies that there is correlation of some sort between the noise samples, which in turn implies that we can take advantage of that correlation to get rid of some of the noise. …
- 12.2k
2
votes
Producing Colored Noise from a given PSD Data
Estimating the necessary filter order
There are methods for estimating the needed filter order for low/band/high-pass filters, but the fact that you are talking about "colored noise" suggests that you … That should make the overall gain of the filter "1" with regards to white noise input. …
- 12.2k
7
votes
Adding noise to an ECG signal
You can control the power of the 50 Hz noise by multiplying the sinusoid by some gain factor (can be less than or more than 1) before you add it to the ECG.
2) I'm not familiar with the Welch periodogram …
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0
votes
Is there an algorithm for second order filtering of data where the filter frequency is not k...
Yes, you can do a second-order low-pass filter without using lots of memory. The key is to use the fact that convolution is a linear operation. You want to do the following:
$$
y(t) = (x(t)*f_1(t))* …
- 12.2k