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Numerical analysis of a digitized signal

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10 views

Eigenvalue decomposition/SVD and the filtering perspective

I have been studying the SVD algorithm recently and I can understand how it might be used for compression but I am trying to figure out if there is a perspective of SVD where it can be seen as a low ...
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0answers
11 views

Estimate Convolution Filter Formula from Noisy Input and Output

When I learned signal processing, I learned how to calculate the output with given input and given convolution filter. However, if now I have the noisy input and output, assuming the system is linear ...
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18 views

Is there a concept of weakly periodic in stats? If so, what is it called?

Ok, say we have a signal that reoccurs within every T+x time where T is a constant and x is a random number small in size compared to T. We know that a function is actually periodic if F(x) = F(x+T), ...
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0answers
35 views

Comparing PCA representations between low-pass and high-pass filtered time-series data

I am currently trying to reduce the number of variables I input into a vector autoregressive (VAR) model. For those that don't already know, VAR models are used on time-series data. My primary concern ...
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26 views

Developing algortihm/model to identify thin linear features in aerial imagery [closed]

I am exploring the possibility of identifying fencelines from NAIP aerial imagery (GSD = 0.6m). I have tried some basic processing in OpenCV using canny edge detection that was detailed in a question ...
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1answer
30 views

Verifying Time Warp

Time warp has been widely assumed in domain of speech processing. If $Xw(t)$ represents a time warped version of $X(t)$, then $Xw(t) = X(t-w(t))$ where $w(t)$ is an arbitrary function with a banded ...
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7 views

How to find the frequency at which loudness levels are varying the most?

I have a dataset consisting of loudness level readings of the sound produced at a national highway, taken on a per second basis at different frequencies(20Hz to 10,000Hz). I have to find out the ...
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8 views

Parameter estimation of time-dependent R.Vs(random processes),

I have taken a number of probability and statistics courses which cover estimation and basic random processes but something which is not clear is how you can do parameter estimation for time-dependent ...
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1answer
36 views

Does mutual information capture interactions?

Suppose I have a response $Y$ and two features, $X$ and $Z$. Individually the features are not very predictive but their interaction is strongly predictive. Something like $$Y = 0.5X + 0.5Z + 20XZ + \...
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1answer
93 views

Filtering out bursts with a consistent range from a time series

I have time series of bursts that look like this: … and zoomed in: Now, there are also spurious bursts (which I call noise) in the data, which look like this: … and zoomed in: As you can see, the ...
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12 views

When doing feature selection based on mutual information, should it be normalized?

Are any kind of normalizations useful when using mutual information to select features? The Wikipedia page has a few variants but they don't seem helpful. The entropy of the response is a constant ...
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3answers
246 views

Usage of Hidden Markov Models

I have a set of questions regarding how HMMs are used. Context: there is a stream of real numbers or real number vectors (e.g. data from a phone accelerometer) and the goal is to detect that an ...
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66 views

covariance matrix vs correlation matrix for multiple signal analysis

I'm dealing with a set of +100 input signals, and one output. I want to explore how each of the signals affects the output. Should I focus on covariance matrix, or correlation matrix, and why? I ...
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21 views

Spatial Transformer Networks and Data Augmentation

The famous Deep Mind paper STN allows for input data transformation, as seen in https://pytorch.org/tutorials/intermediate/spatial_transformer_tutorial.html does not apply input transformation to the ...
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0answers
8 views

Group model from subject level model

I have several subjects in an experiment, for each I have several samples (~50) for reach subject of some physiological high dimensional signal (d=70) which I want to classify to 2-3 classes. When ...
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1answer
20 views

Is (1 - Coherence) a metric, at a given frequency?

I'm performing some signal analysis and was using coherence (magnitude-squared coherence) to inference signals similarity. Now, I need to extend the framework by introducing a metric. I was wondering,...
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0answers
52 views

What is the differennce between invariance to translation, covariance to translation and equivariance to translation?

I get stuck at understanding the difference between invariance to translation, covariance to translation and equivariance to translation in the context of of convolutional neural network. What does ...
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2answers
52 views

What features are suitable when predicting user preferences for songs?

I have a data set consisting of 1240 audio files (30 seconds each) and a file like this (two first rows): u v decision 1 323 0 12 9 1 ...
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2answers
61 views

Features for multi-channel time series classification

I am quite confused about extracting features of the multichannel signals and wonder if anyone can help me out. I want to get a feature set where feature is related to time, but I found the only way ...
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0answers
39 views

Is Spearman's rank and RMS error an appropriate measure of similarity between two signals?

I am working on a project comparing the accuracy of two imaging techniques to measure displacement. I have attached a graph comparing the displacement measured by both techniques over time. I am ...
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1answer
124 views

Time Series Classification with Varying Sampling Frequency

I'm new to signal processing and am wondering how to deal with a time-series classification problem when I have unequally spaced data. Skimming through recent literature, including The great time ...
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1answer
168 views

How to combine multiple signal data in my ML model?

I'm doing a task where I need to work with healthcare data from a few different sources. For example, one is an audio signal recording while another is biometric signal reading such as ECG. Both of ...
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0answers
19 views

Time alignment of two signal with same length

I have found information about similar topics, but wasn´t useful for me. I have the next 2 signals registered by a laser profilometer. As can be seen in the picture the signals are almost equals but ...
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0answers
14 views

Clustering of an image sequence of a moving object

I have a set of 100 images of a man moving on the street. I remove the background and try to cluster the man using dbscan in each image seperately. Instead of getting one cluster (for the man), I get ...
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0answers
31 views

Performing the moving average filter on a set of tracked position data of particles

There is a matlab tutorial on the Moving Average Filter here: https://uk.mathworks.com/help/signal/examples/signal-smoothing.html The tutorial illustrates taking the average of the temperature of ...
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0answers
23 views

Full frequency space description of a continuous-time random process (e.g. signal) in

I don't know if signal processing or math would be a better forum, but I'll start here. Consider an ensemble of stationary random processes $x(t)$ that has the following properties: The PDF is $P[x]$...
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1answer
136 views

Intervention/Level Shift detection

I don't really know if this problem can be considered as an intervention detection/analysis problem. The data shown below is actually a sensor signal collected from an air booster. The air booster has ...
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0answers
60 views

How can I get the cumulant expression from the recursive relation between cumulant and moment?

I am reading some paper about high-order statistics https://link.springer.com/article/10.1007%2Fs11004-009-9258-9?LI=true. The paper gives two recursive expressions relating the multivariate cumulants ...
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78 views

estimating weights in lattice recursive least squares (LRLS)

I'm struggling to estimate the weights (W) from the forward and backward prediction coefficients (k) in Lattice recursive least squares (Lattice-RLS). The standard recursive least squares (RLS) ...
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1answer
26 views

Time series data - A metric to quantify a signal's intensity frequency and duration

I have an time series data with an appearance of a headache events over time. Each headache is characterized with intensity (1-5) and duration (in seconds). Therefore, the signal is represented in ...
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0answers
72 views

Calculating heartbeats per minute from a .wav file [closed]

I am working on a machine learning project relating to heart-Arrhythmia's. I want to be able to calculate heart beats per minute from a 30 second wav file as input. I am creating a mel-spectrogram ...
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0answers
21 views

Output SNR of noisy match filter

A match filter produces the highest output SNR. If $x[n] = s[n] + w[n]$, where $s[n]$ is a signal and $w[n]$ is additive white Gaussian noise, then the match filter for this signal is defined as $h[n] ...
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1answer
106 views

Denoising technique for signal with beforehand known shape (linear and exponential)

I have a noisy signal which is linear and then exponential. I know the type (Gaussian additive noise) and degree (0.01) of noise. Part of the challenge is determining when the signal changed from ...
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2answers
298 views

ICA, how to check for Gaussian components?

Independent Component Analysis (ICA) requires that at most one of the additive subcomponents of a multivariate signal is Gaussian. If I do not know the distributions of the subcomponents, how do I ...
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1answer
552 views

Finding out frequency of peaks using the Fourier transform

I have a signal that varies in time as shown below. I have just shown a 5 s interval of data (from 97 s to 102 s). The sampling frequency is 1000 Hz. My goal is to find out the frequency of the ...
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0answers
94 views

Autocorrelation Exponential Decay Rate for feature selection

I have signals of a time series of length 50. I want to give a try to a PCA like method for classification extracting features from the signal. I am considering several summary descriptors (e.g, mean, ...
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0answers
62 views

How to estimate cutoff point for continuous varibles and binary output?

I have a simulated dataset comprising signals (binary) and a set of continuous inputs. When the continuous var goes up over than a threshold, the system is switched on, which means that the signal ...
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1answer
43 views

Why is phase reconstruction considered hard

I am studying deep learning models for single channel speech separation. I come across several recent methods: Permutation Invariant Training Deep Clustering Deep Attractor Network All of these ...
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0answers
34 views

Kurtosis to detect non-random signals in a spectrum

I have a spectrum that was created from a time series using the FFT. The spectrum has several man-made "channels" in it; some of these are one-bin wide, some are several adjacent bins wide (larger ...
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14 views

Digital Signal Processing DSP Overview support documents

Well, I couldn't find better expression to say what I want :( I'm looking for a DSP study source, that doesn't dive too deep, and covers "all" or most of DSP topics, I just want to have an overview ...
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1answer
84 views

For two stochastic process $x_t$, $y_t$, how can the cross-covariance function between $x_t$ and $y_t$ at lag k different from that at lag -k?

For two stochastic process $x_t$, $y_t$, how can the cross-covariance function between $x_t$ and $y_t$ at lag k different from that at lag -k? For some reason, I can't scrape my head around this. ...
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35 views

Signal to Noise Ratio of a train of pulses

My signal was a train of rectangular pulses consisted of eight pulses with interval between pulses of 36 s with a temporal resolution of 0.1 s. I added a Gaussian noise oscillations with zero mean and ...
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1answer
131 views

How to explain exponential plus Gaussian noise

I have some noisy signal. When I substract real (for calibration it is known) or filtered signal I get residuals. When I plot distribution of these residuals I see that it is sum of exponential and ...
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0answers
130 views

Trying to find a pattern given multiple FFT data sets using Amplitude, Frequency, and Phase

I have about 90+ audio files that I have the FFT data in frequency, amplitude, and phase. I'm trying to find patterns that are found throughout the 90+ audio files but I'm at a loss. I can create ...
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2answers
125 views

Efficient way to detect outlier peaks in periodic signal

I have a set of traces (1D array), and i need to align them, the problem is that, using generic methods ( cross-correlation, dynamic time wrap), would be very slow to align 1 million trace, each with ...
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1answer
66 views

how we input speech signal waveforms in two deep learning algorithms?

I am working with deep learning algorithms like CNN and RNN.I always wonder what is the best way to input wave form type data in to the deep learning algo. I know there are methods like wavelet or mel ...
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47 views

Time-series Decay identification

Are there any known techniques or methods to extract and identify decays from a time-series of data? By "extract and identify" I mean finding similar features as those in the blue boxes in the ...
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14 views

Predicting instantaneous ECG Signal

I have an ECG signal and want to predict the nth instance of signal based on previous m samples. Which of these (or some other) solution will be best suitable for it: Using past m samples as ...
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1answer
63 views

About solving a convex optimization problem

Is there any solution for the following convex optimization problem?: \begin{equation} \text{argmin}_{\mathbf{X}} ||\mathbf{X} + \mathbf{Y}||_F^2 + \lambda ||\mathbf{Z} - \mathbf{FX}||_1 \end{equation}...
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1answer
183 views

mutual information of two identical signals [duplicate]

library(infotheo) > mutinformation(c(1,2,3),c(1,2,3)) [1] 1.098612 > mutinformation(c(1,1,1),c(1,1,1)) [1] 0 Why is there a difference? I keep reading that ...