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.
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Optimally stratifying training, validation and testing samples using simulated targets
I'm fitting a large-scale (both in size of sample and input vector) single hidden-layer feedforward neural network on simulated targets, $\tilde{t}_{\tilde{n}} \in \{\tilde{t}_1,\cdots,\tilde{t}_\...
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Anisotropic noise in gaussain process prediction
In GP regression we predict using $\mu^* = ... (K(X,X)+\sigma^2I)^{-1}...$
This is fine when the noise $\sigma$ is a scalar, but I am confused about what happens when $\sigma$ is anisotropic.
$K(X,X) \...
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21 views
Bias in estimation of a latent / hidden variable drawn from a skewed distribution: what is it called?
I observe a bias effect in my measurement system that I can explain and correct using a simple latent or hidden variable model. I am sure this kind of effect has been described earlier in other fields ...
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1answer
16 views
Remove subtractive noise
I have a dataset that I'd like to remove noise from. All the noise is subtractive, so the ideal value would always be greater than or equal to the measured value.
The following chart shows the raw ...
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2answers
124 views
Noise in regression problems and ways to reduce it
In the theory of bias-variance decomposition for regression problems (this page is a very nice reference on this theory) noise is defined as
$$\mathrm{Noise} = \mathrm{E}_{X,Y}[(Y - \mathrm{E}[Y|X])^2]...
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1answer
37 views
Autoregressive model with observable noise
The classical autoregressive model is a linear model for the dynamic variable $x$, where the added noise $\epsilon$ is directly affecting the dynamics of the model
$$x_{t} = \sum_i \alpha_i x_{t-i} + \...
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26 views
How to extract noise parameters from $y = kx$ data, with multiparameter noise components
I'm interested in extracting noise parameters from (x, y) data, where x are known input values and y are the corresponding signals. There is strict linear relationship between y and x; in the absence ...
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25 views
How to remove the covariance of two measurement methods in order to separately estimate the variance of each
I wish to compare two different methods of measuring an underlying property, and wish to extract the variance of each method of measurement, independent of the other.
The problem is how to correctly ...
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48 views
Are colored noises correlated / uncorrelated?
Let, x be a random variable (r.v) that is white Gaussian, has a flat power spectrum. y can be any colored noise. I think another ...
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1answer
52 views
Coordinates from noisy distance matrix?
I have a black box in which I know there is a 1D line and points along this line, and as output from this box I can get out a distance matrix for the points, but I know there is noise in the estimate ...
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19 views
What is the meaning of noise in a dataset with no dependant variable?
My understanding of noise & signal comes from the context of bias-variance tradeoff in supervised methods.
But given a dataset with no dependant variable, how do you define noise? & how do you ...
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16 views
best hypothesis for data with zero mean noise is the one which assumes no noise at all?
In an ml-class, they introduced overfitting with an example:
Say, we have
$x$ picked from $Uniform(0,1)$
$v$ random noise, picked indepidently of $x$ from $Uniform(-0.3,0.3)$ and $\mathbb{E}[v] = 0$
$...
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2answers
100 views
Seeking recommended literature search terms for a solution to a specific kind of data structure?
Hopefully this isn't considered too off-topic. I'm working in industry these days and came up with a solution to an analysis problem we'd been facing. I'd like to get a sense as to whether said ...
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23 views
What is statistical difference?
In the paper "Calibrating Noise to Sensitivity in Private Data Analysis" by Dwork et al., the term "statistical difference" is used as following (in page 280):
Finally, if a $1 ā \...
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What is the name of this data denoising method
I've been working on extracting data from an extremely noisy signal. The signal itself is the 1st derivative of raw mean squared (RMS) of an audio that may contain segments with some single low ...
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Separating signal from noise: noise models in standard deep learning
In a regression setting, one wants to identify some model of a process of interest, based on noisy measurements. The model usually goes like this:
$$ y_i = f(x_i, \theta_1) + \varepsilon_i.$$
Here, $...
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4answers
277 views
Relationship between overfitting and robustness to outliers
What's the relationship between overfitting and sensitivity to outliers? For example:
Does robustness to outliers make necessarily models less prone to overfitting?
What about the other way around? ...
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53 views
Can RMSE be greater than standard deviation of noise
I am working on model selection problem for noisy data sets. I am having non-parametric models like SVR, regression splines etc. which have can overfit if the hyperparameters are not tuned properly. I ...
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30 views
How to calculate the similarity of data with noise?
I'm stuck on calculating similarity. Please tell me in which direction to move.
There are three files of different lengths that need to be compared for similarity.
It is supposed to use the cosine ...
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2answers
288 views
Linear Regression for Noisy Data
I have noisy dataset collected from a source and I am planning to fit a regression to this dataset.
The dataset has Y and X1 variables (both continuous between (-1, 1)) and I plotted a scatter plot to ...
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10 views
Beta adjustment for added noise
Let's say we have a model that takes the following form:
$$r_t = \sum_{i=1}^N (w_i \times \beta_i \times f_{t,i})$$
Now I'd like to add a noise term $z_i$ distributed normally with $(0,\sigma)$:
$$r_{...
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6 views
Bayesian optimization with offline stochastic function and sticky decisions
Is there a bayesian optimization (BO) framework which allows:
1. Warm start with offline data
2. Stochastic function f(x) is noisy
3. Every iteration is n samples controlled by agent and there are ...
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2answers
30 views
why model perform slighty worst after removing co-related features
I have a classification problem on which I am testing the main classification models like Logistic Regression, SVM, KNN and deep neural networks.
I have a feature set of 40.
And around 5-6 are ...
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33 views
How does a probability distribution change when adding Gaussian noise?
Instance Noise is a trick for stabilising Generative Adversarial Network (GAN) training.
In this paper, the authors say that (page 14, fig. 6)
Instance Noise broadens the support of both ...
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3answers
79 views
Calibration of correlation
Let's say there are two random variables (for example, two time series data of S&P500 and a stock) and their correlation is 0.95. What is the best way to reduce the correlation between these two ...
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10 views
Fourier transforms for noise reduction
Given a signal, which is regularly sampled over time and is noisy. The standard method is with a Fourier transform to reduce the noise and minimise the change to the signal.
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22 views
PCA to reduce Noise on usps data set, problem with the eigen values
I am currently working on PCA. My main task is to apply Gaussian noise to the usps data set and then denoise it by using PCA. The concept is pretty clear, but I am struggling with the eigenvalues plot....
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15 views
ICA for Noise Reduction over a Dataset
Suppose my dataset consists of $N$ example vectors $\mathbf{x}_{1}, \ldots, \mathbf{x}_{N}$ where $\mathbf{x}_{n} \in \mathbb{R}^{p}$ $\forall n$. I assume that each vector $\mathbf{x}_{n}$ is ...
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1answer
38 views
Can a random variable be expressed as a sum of deterministic and random variable?
Say we have a sequence of random variables $\{X_t:t\geq 0\}$ following an unknown stochastic process with distribution $X_t\sim N(\mu_X,\sigma_X^2)$. This idea came to me from the additive noise model....
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0answers
19 views
Extreme Image Noise Removal
I've been trying to solve a noise removal (from images) problem using deep learning and I've tried a lot of the newer architectures for noise removal including FFDNet, NLRN and MWCNN. The problem is, ...
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16 views
How can i compute noise (1 sigma error) given a signal
I have a signal organized as an image, i.e. a matrix. Each "pixel" has an error $\sigma_{i,j}$. Simplifying, let's assume that the error is the same for all the involved "pixels".
How can I compute ...
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21 views
How to estimate the fluctuations in a data?
The question is more about an method of extracting relevant "universal" information from multiple experimental data.
Let say, for every $\alpha$, we have a function of the form
$$f_\alpha(t) = g_\...
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40 views
Simulation from generalized linear model with specific signal to noise ratio
I am trying to simulate from a generalized linear model (GLM) in a specific signal to noise ratio (SNR) setting, but run in to problems if I try to define a reasonable SNR for non-Gaussian data.
In ...
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1answer
50 views
Adding a vector of values to encoder output in autoencoder (keras)
I am experimenting with autoencoders for a very specific application, but cannot unfortunately go into the specific details of what I am doing yet (fingers crossed I can do so after I make some ...
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14 views
Procedure to Smooth Noise for Threshold Values
Suppose I am looking at an estimate $\hat\beta$ in a clinical trial data.
With $a=.05$, a patient with $\hat\beta>1$ is considered to have some medical condition.
A daily example could be a 24-hr ...
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24 views
Research on neural networks mimicking behavior
My question is regarding neural networks mimicking noise specifically.
The idea.
I have clinically clean image generated by a ray tracer and a neural network (type does not matter) that is mimicking ...
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1answer
425 views
What is Massart Noise?
One of best papers during NeurIPS 2019 - Distribution-Independent PAC Learning of Halfspaces with Massart Noise mentions Massart Noise in the title. What is this type of noise? How is it different ...
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1answer
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NaiveBayes: Adding a new predictor which is random noise
In the NaiveBayes method, can adding a random noise vector where each element is sampled from, e.g., a standard normal distribution, help? In what cases this may be a 'clever' approach?
I imagine ...
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20 views
Ornstein-Uhlenbeck process inside boundaries
I have some simulation of the Ornstein-Uhlenbeck process:
...
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0answers
24 views
Learning from āsimilarā data points
Suppose we have predictor variables $x_{i,1}, x_{i,2}, ..., x_{i,m}$ and a response $y_i$ for $i = 1, ..., 1000$.
However, $y_i$ is inherently stochastic in nature, and needs to be represented by ...
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27 views
Math for Gaussian noise on top of another Gaussian noise
I have worked on this project for a while and I have some results. However, I want to communicate in my paper the mathematics involved.
When an image is introduced with 11 standard deviations, this ...
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14 views
Adding noise to existing noise
I have been working on a little project for myself. It involves adding the following noise types to images: Gaussian blur, Salt and Pepper, and Speckle. I know that there exists some fancy formula for ...
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39 views
Laplacian noise applications
I would like to know whether Laplacian distribution can be used to model a Poisson noise.
I have met this case while checking this book and here what it says (see the picture below)
As far as I ...
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1answer
45 views
Median or mode for measurements with erroneous outliers
Background: I am working with real measurements that likely contain two sources of error, (1) measurements that were performed incorrectly, and (2) natural variability of the measured quantity and ...
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0answers
60 views
Log of cost function converges to 0 and is extremely “noisy”
I'm writing my very first NN algorithm to solve a regression problem. I have a signal I would like to use a NN to find its correlation with eight other signals (along the line as f = f(x1, x2,..., x8))...
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60 views
Maximum level of label noise for binary classification so that dataset is “Learnable”?
Assume we have an imbalanced dataset (minority label frequency 1-20%), where subset of samples have their labels randomly flipped. Now, of all samples with positive label (the minority class) in this ...
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16 views
Addings noise to emperical distribution
Say I have the following samples from a joint distribution (note I only have access to the samples and not the functional form of the distribution it self)
...
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1answer
13 views
Is there a good measure of “paternless-ness” in a set of data?
This may be a slightly open-ended question, or even a bad one, but are there any measures of looking at a set of data and seeing whether there is any kind of pattern or not?
For some context my ...
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Timing Jitter of Counter Query … verify hypothesis / noise reduction
I am measuring traffic on an interface every 5 minutes, but the data platform is having an issue with the SNMP data. I think it is caused by timing jitter ... where the data platform queries the ...
