Questions tagged [signal-processing]
Numerical analysis of a digitized signal
0
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0answers
18 views
How to test whether event A affects the frequency at which event B occurs
I conducted an experiment in which I measured the occurrence of some event A over time. I then intervened in the system, periodically introducing event B.
I hypothesise that event B affects the ...
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0answers
29 views
How to generate a new different noisy signal, given a existing noisy signal? [closed]
Assume that a noisy signal, Y = s + n is given, and the aim is to generate another variant of this noisy signal but having the minimum impact on the clean component, s. On other words, is there any ...
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1answer
19 views
Terminology: Is DTW considered to be machine learning or signal processing?
The DTW Wikipedia article puts this method in the category "Machine learning algorithms". On the other hand, the famous paper "Dynamic Programming Algorithm Optimization for
Spoken Word Recognition" ...
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0answers
5 views
Speaker normalization of features before model training
I am building a model using a supervised machine learning based on features I extract from speech signals.
The features include MFCC, auto correlation and energy derivatives.
According to this paper,...
17
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4answers
4k views
Is it a good idea to use CNN to classify 1D signal?
I am working on the sleep stage classification. I read some research articles about this topic many of them used SVM or ensemble method. Is it a good idea to use convolutional neural network to ...
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1answer
48 views
Strange accuracy graph
I was training my NN when I found out something I CAN NOT understand. My net is a bilstmLayer and a softmaxLayer layer with 10 MaxEpochs and 150 MiniBatchSize. I want to classify 4 different type of ...
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0answers
21 views
Variances add, and therefore subtract?
Variances add, so va + vb = vc. If I know what va and vc are, can I estimate vb by vb = vc - va ?
More specifically, I have a noisy statistical time series which consists of the pure signal plus ...
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0answers
12 views
Constructing signal vector of EWMA
I have daily stock returns related to sectors. At the end of each month I want to construct a vector of signals using the past data with different methods over different moving windows like EWMA over ...
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0answers
9 views
Signal processing of data which fluctuates
I have a system which measures weight of plants. The weight is measured through four weight cells on a "plate".
A spray is applied for 3 seconds from under the plate, and waits 60 seconds for the ...
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1answer
14 views
How to deal with varying number of intervals and hence varying number of features dividing an audio signal while classifying these audio signals?
I've $2000$ audio signals, each divided into a number of time intervals/time frames of $50$ miliseconds (ms) and these signals have overlaps for $25$ ms. Now, the audio signals being of different time ...
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0answers
18 views
Clearing out errors from a data set
Sorry for the vagueness of the title, I am having a hard time even coming up with sort of problem I am facing (if there is a specific name for it....)
In a nutshell, I have a time series of points, ...
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1answer
20 views
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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0answers
10 views
Demonstrate the mean of the sample variance
Let's suposse I have a vector of elements $x(n) = \{x(1), x(2), \cdots ,x(N-1)\}$ from a random process X of mean $\mu_x$ and variance $\sigma_x^2$. I want to see if I can stimate the mean and ...
1
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1answer
14 views
How to use GMMs for acoustic signal classification?
There are a number of applications of the Gaussian Mixture Model (GMMs) to acoustics/audio data for the purposes of classification; ex paper1 and ex paper2. GMMs ...
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0answers
6 views
Degree of freedom of estimated sotuioin to the total variation problem from the ADMM algorithm
The study of the total variation problem is to solve the following problem:
$$
\text{minimize} ~ \frac{1}{2}||x - b||_2^2 + \lambda * \sum_i^N |x_{i+1} - x_i|
$$
where $x$ is the unknown, $b$ in $R^...
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0answers
19 views
Find roots of regression function
Physical problem: Signal data comes from several sensors (e.g. 4) and there is empirical knowledge, that data of one of them (e.g. "productivity") depends on other data. Signals of other sensors could ...
2
votes
1answer
55 views
Detection of music note sequence in audio signal
I have an audio signal which contains the combination of different western music notes(I know this combination in advance) and I want to identify the sequence of the music notes present in it. For ...
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0answers
31 views
What is matching pursuit algorithm?
I would like to know What is matching pursuit algorithm?
I did search via different sources but no understandable explanation is available!
Can anyone help with this, please?
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0answers
22 views
Roughness of time series or physical measurements
I am facing regularly the same issue regarding the stability of my physical measurements. How stable is my equipment? How noisy is my signal?
For example, I apply a current on a resistor and want to ...
0
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0answers
26 views
Additional Property of Singular Value Decomposition
I am new to SVD so forgive me if the question is trivial. Following is my question. If I have two sets of linear equations,
Y1 = T1.X
Y2 = T2.X
where T1 and T2 are mxn rectangular matrices. Now let'...
0
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0answers
19 views
Significance testing of signal-to-noise ratio
I have three 18-second, 32-channel resting state EEG time series sampled at 500 Hz using dry EEG electrodes (condition 1) and three more 18-second, 32-channel resting state EEGs also sampled at 500 Hz ...
0
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0answers
27 views
Matching Pursuit & Boosting: Exponential Convergence?
In the paper by Bühlmann BOOSTING FOR HIGH-DIMENSIONAL LINEAR MODELS, he introduces an algorithm, called componentwise linear least squares, and relates it to the Matching Pursuit algorithm by Mallat &...
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0answers
35 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
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0answers
14 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), ...
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0answers
57 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
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0answers
31 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
39 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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0answers
11 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
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1answer
67 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
99 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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0answers
18 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
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3answers
287 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
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0answers
83 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
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0answers
59 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
10 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
37 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
117 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
73 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
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2answers
124 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
59 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
252 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
231 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
24 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
19 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 ...
1
vote
1answer
262 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
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0answers
103 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
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0answers
105 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
33 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
106 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 ...
