Numerical analysis of a digitized signal
0
votes
0answers
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 ...
0
votes
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 ...
1
vote
0answers
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), ...
1
vote
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 ...
2
votes
0answers
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 ...
2
votes
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 ...
0
votes
0answers
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 ...
0
votes
0answers
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 ...
0
votes
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 + \...
0
votes
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 ...
0
votes
0answers
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 ...
2
votes
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 ...
1
vote
0answers
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 ...
0
votes
0answers
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 ...
0
votes
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 ...
1
vote
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,...
1
vote
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 ...
1
vote
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
...
0
votes
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 ...
1
vote
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 ...
1
vote
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 ...
1
vote
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 ...
0
votes
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 ...
1
vote
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 ...
0
votes
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 ...
0
votes
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 $P[x]$...
0
votes
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 ...
2
votes
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 ...
1
vote
0answers
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) ...
0
votes
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 ...
3
votes
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 ...
0
votes
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] ...
0
votes
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 ...
1
vote
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 ...
2
votes
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 ...
1
vote
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, ...
1
vote
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 ...
0
votes
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 ...
0
votes
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 ...
0
votes
0answers
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 ...
1
vote
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. ...
0
votes
0answers
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 ...
0
votes
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 ...
0
votes
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 ...
0
votes
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 ...
0
votes
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 ...
1
vote
0answers
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 ...
0
votes
0answers
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 ...
1
vote
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}...
1
vote
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 ...
