Questions tagged [noise]
noise is a term used for the error term in statistical models and in signal processing. It could be white noise, colored noise or otherwise.
159
questions
2
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1answer
29 views
What does add Gauss Random Noise mean?
I'm reading a article about LSSVM and in numerical part they created an artificial example and it says:
The two features of samples are uniformly distrubuted in $[0,1)$ and $(1,2]$ with 50% of Gauss ...
0
votes
0answers
22 views
Modeling background noise with a half normal distribution
I'm working with radiation measurement data and have background noise data with $(\mu, \sigma)$ < 1 and all background measurement values >= 0. If I wanted to approximate/model this noise, would a ...
2
votes
1answer
63 views
Removing noise using a control sample
I have some measurements of displacement vs time of movement of a particle. Between these measurements, I have some particles that are supposed to not be moving at all (these are the control samples). ...
6
votes
1answer
46 views
How i add uniformly distributed noisy attributes to data set?
I want to add some artificial outliers to my data set by follow same method below.
so, how i can add contaminated data statistically to real data set like Pima Indians Diabetes?
info:
Pima Indians ...
0
votes
1answer
16 views
General Advice - Neural Network Optimization for Noisy Label Training
I'm new to Neural Networks. Trying to get some general advice.
Multi Class, 3 classes
Has noisy labels, with somewhere between 60 and 80 percent accuracy
Huge amount of training with the issues ...
0
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0answers
22 views
Find plausible peaks in streamed data
i have got a signal of a streamed source which produces values like in the picture.
I want to get the "real" peaks (blue circles).
But the noisy peaks (red circles) mess up the peak search.
The ...
0
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0answers
27 views
How can I reduce the noise of prediction graph? [duplicate]
I am trying to use LSTM to predict a time series data as you can see in the following image, the predicted graphs is very noisy:
The original data is looking like this:
That I normalized it like ...
0
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0answers
26 views
Modeling of signal with noise near zero
I would like to know if there is a standard formula/representation for handling/modeling something like Gaussian noise near zero. If you have a signal that is always positive which has some noise on ...
0
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0answers
8 views
power spectrum density (V**2/Hz) for nonuniform logarithmic array?
I have nonuniform logarithmic time data array which have 1000pts/decade. that means sampling rate is changing in each intervals or decade.
How can I calculate and plot power spectrum density (V**2/Hz)...
0
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0answers
15 views
RNN outputs noisy predictions
I have an RNN that I've trained and I'm now using to generate new sequences. These sequences are basically discrete state time courses for K different states. The ...
1
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0answers
108 views
Techniques to apply Discrete Wavelet Transform (DWT) to denoise and predict time series
I just started playing with wavelets and have been using this library (https://github.com/rafat/wavelib) to further my understanding and see if 'denoising' the series at all possible levels is ...
0
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0answers
19 views
What is the effect of noisy labels in distant-supervision?
I am just learning about distant supervision. I read the paper of Mintz et al. and trying to get some intuition of how the noise influences the classification.
My general assumption is, that having ...
0
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0answers
18 views
Bayesian vs Frequentist inference in the presence of noisy data
I'm wondering how Bayesian inference and Classical/Frequentist inference fair towards noisy data. I can't seem to find too much literature addressing this issue and it seems the conclusion is usually ...
0
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1answer
26 views
Recovering a distribution after Gaussian noise is added
I have a large dataset (400k rows) in which I suspect the data has been obfuscated by the addition of a Gaussian distribution. My guess is that some of the data had categorical variables (based on the ...
1
vote
2answers
57 views
Sensitivity of regression parameters to noise
How sensitive are the parameters obtained from OLS, logistic or other regression methods to noise ?
By noise, I mean minor changes. For e.g. adding a small noise $-1<\Delta<1$ to $\beta_1$ in $...
0
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0answers
29 views
How to perform feature scaling on noise removel process?
i'm working on dataset contain machinery sensor data. each column(feature) represent different sensor data(pressure, temperature, speed, etc) of the machine part. here task is to predict normal ...
1
vote
2answers
60 views
differentially private release of histograms (non-negative valued queries)
Two practical questions arise when releasing differentially private histograms/counts via addition of Laplace/Gaussian noise:
1) Is the result of noise addition truncated/rounded (since we know that ...
0
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0answers
45 views
Noise reduction with known noise distribution
I have a time signal with a known noise distribution parameters (gaussian, sd is known). I would like to estimate the true value statistically and in the best case obtain a confidence interval.
As I ...
0
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0answers
70 views
Prediction of noisy target variable
The target variable for my regression problem has a very high noise, so measurement error is very high and trends can only be seen in longer time periods.
What are good approaches to address this ...
3
votes
2answers
155 views
Regression algorithm on [0,1] with lots of mislabeled data
I have a training set mapping some Likert-scale variables (integers between 1 and 7, rescaled to real numbers between 0 and 1) to predict a continuous variable between 0 and 1. The data set is ...
2
votes
1answer
47 views
Apply 3 sigma formula in gamma distribution?
Let say i have some data that follows gamma distribution, and i calculated the Mean and Standard deviation of the gamma distribution.
I also know that there are some outliers(Noise) in the data i ...
0
votes
1answer
305 views
Noise and Outliers in DBSCAN
Why are noise and outliers treated as the same concept in DBSCAN (density-based spatial clustering of applications with noise)?
2
votes
1answer
263 views
Sum of Bernoulli random variables with Gaussian noise
This relates to a question asked recently where (one of the edits of) the question asked what happens when a sum of Bernoulli random variables has some form of noise on the probability parameter.
...
0
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3answers
69 views
How can I understand the concept of a noise in machine learning?
In Bishop's book, one of the first examples is shown here
Essentially, the data $x$ are randomly generated, and $t$ are generated by running $x$ through a function $\sin(2\pi x)$, then Gaussian ...
0
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0answers
28 views
How sensitive are Neural Networks to weight changes?
Let's consider the space of feedforward neural networks with a given structure: $L$ layers, $m$ neurones per layer, ReLu activation, input dimension $d$, output dimension $k$.
Which means I'm ...
1
vote
1answer
209 views
Calculate threshold value for Poisson distributed noise
I need to calculate a threshold value to get rid of Poisson distributed noise in an image to perform a cluster analysis on the image.
The image is the representation of a signal, whose datapoints ...
2
votes
0answers
201 views
Adding noise to time series data to increase training data
I am dealing with a weekly time series forecasting problem and I am currently investigating the use of an LSTM to make a multi-step forecast for a univariate time series. I actually have a ...
1
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0answers
29 views
Using a neural network for a regression problem, where the model to be learned suffers from awgn
I have currently a neural network to learn a (relatively non complex) system model (vector regression). Its problem is that the outputs of the system suffer from arbitry additional white gaussian ...
1
vote
1answer
39 views
Incorporating noise into machine learning models?
Usually, in machine learning textbooks the $X$ dataset and the target $y$ are defined with exact values.
How about the case if the values of both $X$ and $y$ have noises: for instance, we only know ...
1
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0answers
35 views
Sum of correlated non-Gaussian random variables with same distribution as individual terms
Let's say there is a sum $s$ of $N$ zero-mean correlated random variables $\{x_i\}$:
$$
s = x_1 + x_2 + \ldots +x_N,
$$
where the correlations $C_{ij} = \mathbb E[ x_i x_j]$ are known. Assume that ...
2
votes
2answers
55 views
What is the probability that sample variance decreases by adding random Gaussian noise to the variable?
If we assume WLOG that our variable X has mean zero (mean-centered), then this can be stated
$Pr \bigg(\sum x^2 > \sum (x-n)^2 \bigg)$
for some random variable $n$ distributed under $N \sim N(0, \...
0
votes
1answer
34 views
How to remove cofounding effect on a variable?
I'm working in a team that is collecting data by bicycle : We have biometric t-shirts that measure our ventilation rate.
The problem is that during the last data collection, participants used masks to ...
0
votes
1answer
12 views
Supervised learning with error-range in labels?
I am working in a problem where labels have an error range (we know the range). For instance, a label can be expressed as $y_i \pm e_i$ with $e_i$ is the error range for the label of the instance $i^{...
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0answers
16 views
What determines whether relative or absolute Gaussian noise should be added to data?
Suppose I have some data vector, $\mathbf{d}$ with length $N$. I want to add "Gaussian noise" to the data. My understanding is that there are two ways to do this.
1) Relative noise percentage
$$\...
0
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0answers
769 views
“Add White Gaussian Noise with SNR” vs. “Add 5% Gaussian Noise”
I have a noise-free dataset which is a vector of numbers, $\mathbf{d}$, with length $N$.
I want to "add noise" to this data. My understanding is that there are two ways to do this.
1) Add some ...
3
votes
2answers
30 views
Formula to detect non uniformity noise
I have this line profile, how is the best way to detect this kind of non uniformity?
I must detect a sudden change, as opposed to the last section that decreases slowly..
But the sudden difference ...
4
votes
2answers
619 views
Correcting Kullback-Leibler divergence for size of datasets
We have the following implementation of KLD:
...
0
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1answer
39 views
Why adding noisy predictors improves my random Forest prediction?
I am doing some tests with randomForest and I cannot understand the following results :
...
0
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0answers
27 views
Optimization of a noisy function with binary output
What frameworks exist to optimize the following problem:
$\theta^\ast = \operatorname*{argmin}\limits_{\theta \in \Theta} f(\theta)$
with the characteristic that $f$ is noisy and has a binary output ...
1
vote
0answers
49 views
How do you use the predictive distribution with noise in Bayesian Optimization?
I have been reading a paper on Bayesian Optimization, and I was reading the section on adding Gaussian noise to your Gaussian process. The article is:
Brochu, Cora and de Freitas (2010). A Tutorial ...
2
votes
0answers
130 views
What is the difference between Noise, error and residuals?
I was reading about Kalman filter. http://web.mit.edu/kirtley/kirtley/binlustuff/literature/control/Kalman%20filter.pdf
They talk about additive noise and error. I need to understand difference ...
1
vote
0answers
32 views
MIxture model in R to generate noise in data
I have a bit of code in R that adds noise to an harmonic series according to a normal distribution:
...
1
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0answers
37 views
How does Noise affect the results of Transfer Entropy?
I was reading about Transfer Entropy and came across this package: https://cran.r-project.org/web/packages/TransferEntropy/TransferEntropy.pdf
The code in the package:
...
2
votes
0answers
309 views
Awful performance of LSTM on noisy time series after stationarisation
Note. The post is quite long because I added some thought process for the sake of seeing the big picture. So grab a coffee and indulge yourself. For tldr the actual question on the bottom.
I put my ...
2
votes
1answer
84 views
Ridge Regression as Robust Optimization
We were told to assume in class that the below optimization formulations are equivalent-
$$\min_w\max_{\delta:||\delta||_F\leq\epsilon}||(X+\delta)w-y||_2^2$$
$$\min_{w}||Xw-y||_2^2+\lambda||w||_2^2 ...
0
votes
1answer
69 views
Can redundant/irrelevant features be called a Noise?
Let's say we want to predict job applicant' salary. We have a dataset with following features:
{Age, Experience, Education, Astrological_Sign, Weather_Today}
5 features in total.
In this set, ...
1
vote
0answers
43 views
How to add noise to obfuscate patterns in data
I have a program that generates output data depending on the inputs it is given. Lets say the data generated is a list of n items where each item is a natural number between 1 and k. I need to release ...
10
votes
2answers
782 views
Generate uniform noise from a p-norm ball ($||x||_p \leq r$)
I am trying to write a function which generates uniformly distributed noise which comes from a p-norm ball of $n$ dimensions:
\begin{equation}
||x||_p \leq r
\end{equation}
I found possible ...
3
votes
0answers
45 views
Get noise model from true and distorted data
I have been given two data sets:
Set A: a small data set containing data randomly drawn form an underlying
distribution
Set B: a very large data set containing data randomly drawn from the same
...
4
votes
2answers
2k views
Noise in regression data
How can I compare which distribution has more noise than the other. If for example I generate some data, how do I know that it has a large percentage of noise? Here I have a small sample code that ...
