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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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Denoising brownian noise type signal (piecewise continuous noise) at known time samples [closed]

Posting here because I didn't have much success in dsp. Hopefully some of your skillsets might be more valuable in this situation. Original question here: ORIGINAL QUESTION I have a signal which at ...
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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 ...
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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 ...
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1answer
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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 ...
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2answers
47 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 $...
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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 ...
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1answer
35 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 ...
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32 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 ...
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23 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 ...
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2answers
142 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 ...
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1answer
27 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 ...
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1answer
78 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)?
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1answer
79 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. ...
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3answers
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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 ...
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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 ...
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1answer
118 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 ...
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146 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 ...
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25 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 ...
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1answer
36 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 ...
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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 ...
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2answers
52 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, \...
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1answer
33 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 ...
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1answer
11 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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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 $$\...
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434 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 ...
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2answers
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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 ...
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323 views
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1answer
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Why adding noisy predictors improves my random Forest prediction?

I am doing some tests with randomForest and I cannot understand the following results : ...
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26 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 ...
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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 ...
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($L_2$) distance for noisy data

I'm given a subspace $V$ and a set of $n$ corrupted observations $\tilde{x}_1 = x_1 +\epsilon_1,...,\tilde{x}_n = x_n + \epsilon_n \in \mathbb{R}^D$. Assume $D$ is large and that $\epsilon_i \sim N(0, ...
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0answers
61 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 ...
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22 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: ...
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30 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: ...
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190 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 ...
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1answer
69 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 ...
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1answer
59 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, ...
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36 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 ...
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2answers
618 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 ...
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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 ...
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2answers
1k 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 ...
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0answers
114 views

Correcting for noise in gene expression data

I have a training set of RT-qPCR gene expression data (not run in triplicate) for a batch of samples with two phenotypes $A$ and $B$ on which I've trained a logistic regression classifier. I also ...
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2answers
93 views

ARMA models and residual series

Assuming that model is correct, why does the residual series of an ARMA model resemble a white noise process?
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33 views

Time series clustering/segmentation based on pattern

I'm currently working with a database which contains several large PPG (pulse oximetry) and ECG time series. These series, however, contain segments within them which are highly contaminated by noise, ...
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2answers
517 views

Removing gaussian noise from a time-series data

I have a noisy time-series data (Figure 1). As you can see the variance in this data set is very high and the "Gaussian noise" needs to be removed for me to analyze this signal. Normally we apply a ...
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Error of solution ranking

I am exploring subset selection of multi-armed bandits and I am curious about an error measure of a selection. So in the scenario of a multi-armed bandit, a set of arms are present and we aim to ...
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1answer
71 views

Why does “sticky noise” defy averaging attack?

I have read an interesting paper (pdf) describing how a privacy preserving technique might be breached, but I am having trouble understanding the following paragraph describing one of several layers ...
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1answer
58 views

Deal with noise data

The following picture represents a graph with price over time. I am a mathematical student, but also a trader. I want to create a function which could localize the good entry and exit points for sale ...
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1answer
47 views

How to test for differential privacy on multiple choice data?

I apologize I am new to statistics so I do not know all terms and concepts. My current algorithm for adding noise to multiple-choice favorite color data is this: ...
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Expressing Confidence in Conclusions from Noisy Data

I’m working on improving the robustness of a software engineering process that measures performance of programming language compiler and standard library, a.k.a. benchmarks — in the computing sense of ...