Questions tagged [statistics]

Statistics is the study of the collection, organization, analysis, and interpretation of data.

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Stationarity Test on Dataset

I have a nice and clean noise signal sampled at a fixed rate for several hours. When I calculate the PSD I see it's pure flicker noise. But I don't know much about the process. I've seen some ...
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Order statistics: always applicable tool in wireless communication?

I have seen few papers where generalized order statistics is used to obtain statistics of the instantaneous SNR. "Performance analysis of monostatic multi-tag backscatter systems with general ...
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Autocorrelation and the dot product of complex signals

I have a question for the signal processing community. When trying to calculate the autocorrelation of an array containing complex data, could the result be purely imaginary, and is there any ...
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Get shape of a recurring pulse event in my plant video signal

I'm studying plants - specifically how the color of their leaves change throughout a day. I have a camera pointing at a leaf which takes a picture every 47 minutes and calculates the average green ...
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How to interpret arg min in the the following equation?

I am studying the following equation: $$\hat{s}_m(n) = \arg \min_{s_m(n)\in A_s}\left| \frac{\psi_m^H}{||\psi_m^H||^2}y_m(n)-s_m(n)\right|^2\tag{1}$$ here $A_s$ is 1x$N$ vector of QPSK symbols, $s_m(n)...
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Standardizing signals from the same experiment setup with different recording tools

I've been looking to merge two datasets I have, that capture instances of the same phenomenon using two different recording tools. Both are multichannel electrical signals, but the recording tools ...
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27 views

Affine transformation on circularly symmetric Gaussian distribution

Assume the complex random vector $\mathbf{y} \in \mathbb{C}^N$ is circularly symmetric distributed i.e. $\mathbf{y} \sim \mathcal{CN}(\mathbf{0},\mathbf{R})$ $$ p_{\mathbf{y}}(\mathbf{y})=\pi^{-N}\...
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Mann-Kendall Trend Test

I'm using the pyMannKendall package in Python to detect the presence of slope of any given waveform. More details of the package here: https://github.com/mmhs013/pyMannKendall I'm not exactly able to ...
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Particle Filter estimation: sinusoidal signal

I am designing a particle filter for the extraction of a sinusoidal wave with known frequency and sampling frequency from Gaussian noised biased measurements ($y=x+\text{bias}+\text{Noise}$) My state ...
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Help with creating/drawing the PDF of signals X and Y

Given is an analogue source $x$ equally distributed in the interval $[-1;+2]$. By means of a mapping, the signal $Y$ is calculated according to $Y = (X - 1)^3$ is generated. Sketch the $PDF$ of the ...
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How to interpret Allen Deviation with increasing negative slope

I was calculating the Allan deviation (utilizing the Python module allantools.adev, which relies on eq. (6) in https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=50505). The expected behavior is a ...
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Linearity of the system with Pearson correlation sliding window

I have a sampling system that consists of linear and non-linear components(analog filters, ADC, CPU, and so on). I made some HW changes and I want to verify that the linearity was preserved. My method:...
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25 views

How to handle skewness and kurtosis parameters of missing data?

I'm working on acoustic signal classifier. Most signals are characterized by having two echoes (peaks). Each echo can be described by maximum value, duration, skewness and kurtosis. Thus each signal ...
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2 answers
294 views

Quantization error standard deviation

Here I found that "pure" quantization error standard deviation of the signal is $1/\sqrt{12}$ of LSB. Where does it come from?
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Is Allan variance still relevant?

I've been working with Allan variance for a while and I'm not really super excited about is purpose. I understand that noise time recordings, if they include flicker noise, diverge in time. In other ...
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4 votes
1 answer
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Adding Variance \ Weights Information When Solving a Basis Pursuit Denoising Problem (BPDN)

Having a "measured" vector $\mathbf{y}$ with its statistics (counts or variance per element), one can use weighted least squares approach to solve the linear system $$\mathbf{A}\mathbf{x} = \...
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How to use numpy covariance result to get a correction factor and make my second signal to exactly overlap on my first signal?

covariance = np.cov(y1_interp, y2_interp)[0][1] print('covariance is', covariance) covariance is 0.00010861874695023591 This number shows how different my signal 2 ...
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Dividing a data set into segments with consistent inner behavior, using segmentation algorithms and metrics for consistency

Context of the problem: I have signal data which was recorded in a software system and which shows the runtime of multiple processes over time. In total there are more than 900 processes each having ...
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2 votes
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Estimating shot noise - what's the origin?

If I have some photon detector, say a CCD, how do I estimate the error introduced by shot noise correctly? Typically, sources found on the internet say that the shot noise is the square root of the ...
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Infinity values in statistical analysis of minute frequency data

I'm trying to extract statistical features from power spectral density values in Python. My data is actigraphy data with sampling rate 1/60 Hz (once per minute). This is a sample from my data, "...
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Is "Introduction to Statistical Signal Processing" by RM Gray good for starting?

I am working on noise processes in electronic devices for my studies, by now Ive been doing a fairly large amount of processing of time measurements, like calculate PSD, estimate thermal, flicker ...
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Reduce signal length while maintaining properties?

I am new to DSP. So I have a noisy signal with some high-frequency components. I was able to characterize the statistical properties of this signal through a gaussian distribution. My aim is to run a ...
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1 answer
37 views

Is RMS or MEAN appropriate for a DC current signal?

I've extracted SCADA data recording (every 2 seconds) the DC current applied from a DC power supply (Sorenson SGA) during a steady state (current control mode) electrolysis trial. To report the ...
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Is sum of squares of normally distributed Random variables follow Chi square distribution?

Actually standardized variable z of x(which has a normal distrbution) is (x - E(x))/squareroot(E(x-E(x)) ^ 2) In chi-square distribution we have that sum of squares of unit normal distribution ...
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Determination of Variance from Symbol Error Probability Equation

For a M-ary QAM receiver, the symbol with AWGN noise is received and detected with Maximum–Likelihood (ML) Decision algorithm. The symbol error probability (SEP)is approximated as : here, Eb is the ...
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1 answer
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Can Goodness-of-fit increase while noise also increases?

I saw a tweet with a good slide. It has a Goodness-of-fit curve that goes up with Model Complexity. There is a Generalizability curve. Noise is cited as the difference between the GOF and ...
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1 vote
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67 views

Fisher Information Matrix for sinusoidal signal under multiplicative noise

Consider observations ($y$) of a sinusoidal wave with multiplicative noise ($v$) where we are estimating unknown frequency ($\omega$) and unknown initial phase ($\theta$). We can write this system ...
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1 answer
63 views

RF-Chain Signal Delay for Sensor Switching

Lets have a RF-chain as above with system bandwith from HP corner to the green line say 1 MHz. The signal accumulates delay as it passes through this analog chain, and due to it being non-liner filter ...
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1 answer
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Calculating total power for the signal

In my previous question I asked about calculating a single number as "Spectral Density" feature from signal data. We concluded that it is really a total power and article (link) authors ...
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364 views

Trying to implement matlab pwelch function in python using scipy welch

I am trying to port the statistics toolbox function pwelch from matlab into python, but when I am trying to implement it using scipy.signals.welch, it does not return the same results as it does in ...
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50 views

Short Time Fourier Transform has different frequencies than Fourier Transform?

The reason we do the STFT is so that we can analyse for short segments of time how much of the components in the frequencies of the FT are present. However, it may be possible that completely ...
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6 votes
2 answers
332 views

How to Calculate Local Spatial Variance of an Image?

For those who work often on image processing, I'm facing an algorithm of Non-Uniformity Correction (NUC) that requires the calculation of a parameter called "Local Spatial Variance". I can't ...
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Choose the right Sigma for Gaussian filter

I have the following problem: I have a time series with counted data. I now want to smooth it using a Gaussian low-pass filter. Is there a method to determine the sigma value? The window should have a ...
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2 votes
1 answer
210 views

Having problems with understanding the meaning of PSD for colored Gaussian noise

After reading two articles on signal processing stack exchange: On coloured Gaussian noise How the white and colored noise differ in time domain I do understand that variance do not change over ...
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What's the difference between nonstationary and time varying?

I am confused by the following statement from the paper Beamforming: A Versatile Approach to Spatial Filtering by Barry D. and Kevin M.: There are two basic adaptive approach: 1) block adaption ..., 2)...
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2 votes
0 answers
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What is the physical significance of statistical quantities like mean, variance, skewness and kurtosis of a digital signal?

I understood the mathematical meanings of the mean, variance, skewness and kurtosis. But when we calculate these quantities for a signal (say a digital audio signal), what physical meaning do they ...
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1 vote
1 answer
48 views

Effectively extracting “real” data from a noisy dataset

This question was originally posed to Math SE. It was suggested that DSP SE would be more suitable. Background & Motivation: I have three lists of timestamps (UNIX timestamps, plus a subsecond ...
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When is Markov a Martingale

I have two questions and I am very confused about the concepts Can a Markov process of order one also be a a Martingale? Is any Markov process of order one also a Martingale? For 1. I would say yes, ...
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2 answers
67 views

Intuitive definition of ergodicity for random signal

Is it possible to define the ergodicity of the random signal in an intuitive sense without using any statistical reference?
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5 votes
1 answer
75 views

What Are Intuitive Explanations for Shrinkage in the Context of Image Denoising?

I have occasionally come upon the term "shrinkage", mostly in the context of denoising methods. My rough understanding is that it refers to the part where the real distribution might not be ...
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standard deviation of two constant noised signals related through interpolation

Let us say say we have a noised constant signal and want to evaluate the standard deviation (std) of the noise. We calculate the std of the said noised signal and call it $\sigma_1$. Now we process ...
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2 votes
1 answer
153 views

What will be the distribution of a given signal

Suppose I have a signal $$ \mathbf{s} \sim C \mathcal{N}\left(\mathbf{0}, \sigma^{2} \mathbf{I}_{N_{}}\right) $$ The signal going through a channel : $$ {\mathbf{r}}_{}=\mathbf{s}+{\delta \mathbf{n}} ...
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Lower bound of weighted average of sequence

Can anyone prove that $$\mathrm{avg}\left(\frac {a_i}{\left(1+a_i\right)^2}\right) \ge \frac{\mathrm {avg}({a_i})}{\left(1+\mathrm{avg}{(a_i)}\right)^2}$$ for a sequence of positive valued elements $...
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1 vote
3 answers
390 views

Averaging data from 2 sensors

Suppose we take a reading of a single rotating axis using 2 identical sensors. Intuitively, I think that averaging the outputs of both sensors will yield a less noisy result. But what if sensor A has ...
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1 answer
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ML estimation - solve for x

I'm trying to solve the following maximum likelihood estimation but for multiplicative noise instead of additive noise: So the goal is to do ML-estimation for a scalar constant $x$, which is ...
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1 answer
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Statistics to characterize time-domain envelope of acoustic signal

I am interested in comparing 0.5-second 44100/s signals when different ADSR envelopes are applied to them. However, I don't want the comparison to be as fine-grained as simply calculating a 5000-...
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1 answer
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Complex gaussian random variable [closed]

In my work i need to generate circularly symmetric complex gaussian random variables with non zero mean and certain variance in matlab. I know the command for generating in case of zero mean , but ...
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1 vote
1 answer
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Questions in a Character Degradation Model Paper

I have questions in the ‘Noise region definition’ and ‘Noise generation process’ of the paper “A character degradation model for grayscale ancient document images”. In Noise region definition, ...
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1 answer
112 views

Cepstrum of white gaussian noise

What are the statistics of the cepstrum of gaussian white noise? \begin{align}\newcommand{\Nfft}{ {N_{\mathrm{FFT}} }}\DeclareMathOperator{\FFT}{FFT}\DeclareMathOperator{\IFFT}{IFFT} x_i &\sim \...
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1 answer
120 views

Derivation of Circular Mean Square Error

I would like to understand how Eq. (36) in [2] was derived: The rationale behind the definition of circular sample mean in Eq. (37) is clear, but there is no motiviation for the CMSE definition in Eq....
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