# Questions tagged [signal-processing]

Numerical analysis of a digitized signal

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21 views

### Does blind source separation (ICA) work if channels of mixture are observed asynchronously?

Does Independent Component Analysis (ICA - fastICA, SOBI, etc.) work reliably when applied to a multidimensional mixture (observation) $X = (X^1, \cdots, X^d)$ if the different channels $X^i$ of the ...
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### The length of spectral density is longer than the data using spectrum() in R

I'm using spectrum(method = "pgram") in R to calculate the spectral density in my time series. spectrum() returns the spectral density for each frequency(from 1/n, 2/n to 1/2, n is the time ...
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### Why the baseline algorithm irls from the R baseline::baseline() function can generate negative values given a positive signal in input?

I am running the baseline function on the following signal in order to find peaks. Why is the computed baseline negative in some regions?
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### Methods of analysing sensitivity of time-series signal data

I am trying to analyze the sensitivity of the data I got from a power plant model. Assuming I give step signal to different input signals(a,b,c.....), then I got a response of the output power(pa,pb,...
24 views

### Measure prosodic similarity using deep learning

I have a dataset of 12,000 audio recordings of nonnative learners imitating the prosody of native speakers (300 samples for each native speaker utterance). All the nonnative learners' attempts were ...
38 views

### Singular spectrum analysis and their "eigentriplets"

I am struggling to understand why eigentriplets arise when decomposing a signal by using singular spectrum analysis (SSA). The term eigentriples refers to the components of a singular value ...
13 views

### How to compare/ quantify how similarity between wave patterns

I have an idealized wave pattern, and I'm trying to come up with a measure to compare how similar other wave patterns are to it. I'm more concerned with the overall shape and timing of a wave as ...
24 views

### Estimate the Image Using Multi Many Realizations of Its Convolution with a Known Filters Using Wiener Filter

Suppose we have a corrupted image $Y = H*X + \epsilon$ that is formed by taking an image $X$, convolving it with a point-spread function $H$, and adding gaussian noise $\epsilon$. Then we know that ...
46 views

### Calculate similarity between two time series using discrete wavelet transform cofficients

I am new to the field of signal processing but I have read that DWT can be used to find similarity between two time series, I am curious as to what kind of similarity measure do we use once we have ...
16 views

### Normalization, centering and PCA [duplicate]

I have a feature matrix composed of frequency responses (in dB) from individual acoustic events. Frequencies in the columns, events in the rows and the matrix is the response The responses decrease ...
19 views

### I'm confused with cross correlation and covariance of signals

I've heard that correlation is just a normalized covariance buy they can be treated the same. I'm a bit confused about it- I usually calculate cross correlation between two signals just like here in ...
40 views

### How to estimate a parameter from a unknown model as follow?

Recently I have met a question. I have derived a important indicator in my research on radar signal processing. The indicator $y$ can be calculated by another measured value $x$, and their ...
32 views

### How to Add two white random gaussian noises from different noise sources?

I have generated two different white gaussian random noises in MATLAB using two different seeds. For example: Asn1 = sqrt(noisepow1/2)* (randn(size(As))+1i*(randn(size(As)))); Asn2 = sqrt(...
41 views

### Fitting sums of Gaussian-like density functions

I acknowledge that similar question has been asked a couple years ago, yet it still seems unresolved. Ignoring the domain knowledge, the statistical problem behind is to fit a non-linear regression ...
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### how to make Kalman filter results equivalent to linear regression? [duplicate]

Statistics gurus, Kalman filter appears to be a powerful estimator for linear problems. I understand one can tune the performance by adjusting parameters like process noise and measurement noise. Is ...
15 views

### Generation of multiple arrays or vectors with specific correlation among it?

I shall try to elaborate my question as much as possible because I tried multiple things but I am not available to find a possible solution. Problem Statement : I have an impulse response, say a ...
27 views

### Correlation estimation by the Blackman-Tukey method

Problem statement: Assume that the spectral estimation for an unknown signal is given by the Blackman-Tukey method as follows: $$S_x(\omega) = 5+8\cos(\omega)-6\cos(2\omega)+2\cos(3\omega).$$ Assume ...
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### Finding autocorrelation coefficients given PSD values at 2 frequencies

Assuming that $S_X(w)$ denotes powers spectral density function at frequency $w$, we are given $$S_X\left(\frac{\pi}{4}\right)=10+3\sqrt{2},\quad S_X\left(\frac{\pi}{6}\right)=11+3\sqrt{3}.$$ We also ...
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### Is the t-test valid for the real measurement?

I'm working with a real signal measured by a machine. I've compute the mean and standard deviation, it's nearly the same. However the Allan deviation is not good enough. I want to estimate the noise ...
28 views

### Step change detection in signal by convolving with step vector

I am facing the following problem in signal processing and I have run into a wall. I am trying to detect abrupt changes (step changes) in a constantly decreasing signal by convoluting the signal with ...
20 views

### Seeking an algorithm to turn a continues signal into binary

I had a nice project in mind, which I will probably not going to do because of a lack of time, but I had some theoretical problem I faced there, which still bother me and might be interesting for you ...
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### Uncertainty principle in probability theory

In probability theory, there is the covariance inequality $$\operatorname{Var}(Y) \geq \frac{\operatorname{Cov}(Y,X)^{2}}{\operatorname {Var} (X)}.$$ In signal processing, there is a similar ...
44 views

### Help with time series comparisons using periodograms

I have a dataset consisting of time series signals of different lengths obtained from different groups of patients. I am trying to understand the commonalities of the time series of each group. ...
26 views

### 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 σ1. Now we process the signal,...
67 views

### ICA: a question about the non-gaussian requirement

I'm new in the ICA processing and I'm trying to understand the non-gaussian requirement. I read that the problem is that, if the composed data is $\mathbf{x}=\mathbf{As}$ with $\mathbf{A}$ (unknown) ...
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### why is the signal divided into epochs in EEG classification?

I'm new in EEG signal classification. Studying the literature on this topic, I wonder why the EEG signals are divided in epochs, so, instead of classifying the whole signal all at once, we usually ...
18 views

### CTC Speech Recognition Model giving absurd results on actual recording

I have trained a speech recognition model which uses CTCLoss and is inspired from https://www.assemblyai.com/blog/end-to-end-speech-recognition-pytorch I trained it on the Librispeech Dataset (train-...
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### Signal processing: How to patch over dip in signal using R?

I am a biologist starting to use R to analyze my data. Could anybody please help me solve my problem I encountered when working in signal processing in R? Problem I have a recording of a signal in a ...
19 views

### How can I "remove" variability in my data that is due to periodic signals, such as Temperature, RH and Solar radiation?

I have a measured signal that I know is affected by some periodic signals, such as Temperature, RH and Solar radiation. Is there a way that I can "remove" their influence from my measured ...
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### What is a suitable way to reveal correlation between these two signals?

I have two time-domain data signals which look like the following: I know that variations in $x$ are able to induce variations in signal $y$, and would like to be able to show that "yes, x is ...
60 views

### Are the following model assumptions on a data stream too restrictive?

Suppose that you were to model a "generic" continuous-time real-world data signal $X$ taking values in a bounded continuum $K\subset\mathbb{R}^d$ (e.g. the body temperature of a patient or ...
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### 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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### Does it make more logical sense to model the discrete FFT output as a categorical variable or a numerical variable?

I am training a time-series data classifier and some of my features are the output of CT FFT. The results are of course discrete frequencies. I understand that they are in numerical order and higher ...
106 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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### What is the similarity and difference between signal recovery and parameter estimation?

As per inferential approach both are estimation problem. But, in signal recovery, we estimate our input signal from the measured (noisy or noise free) observations. And, in parameter estimation, we ...
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### What are the parameters in signal recovery? Whether source of these parameters are the sampling property of impulse response?

I was reading the following book: Juditsky, Anatoli, and Arkadi Nemirovski. Statistical Inference via Convex Optimization. Vol. 69. Princeton University Press, 2020. Here, I could not visualize the ...
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### Encoding a time series with varying time differences as an image

There are methods to encode a time series into an 'image' i.e a matrix of scalar values. Some methods include recurrence plots, gramian angular field and markov transition field. Most methods assume ...
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### ML model for Signal Decomposition [closed]

So recently I got a task which can be summarized as follows: Suppose we have 3 functions f1, f2, f3 and a certain combination of the functions gives us ...