Questions tagged [signal-processing]

Numerical analysis of a digitized signal

Filter by
Sorted by
Tagged with
1
vote
0answers
54 views

What is the laplace transform of the below given PDF?

Really am interesting to know more about statistical properties of the following PDF , of the Random variable $z$: $$F(\sigma,\mu,z)= \frac{(z-\sigma )^2 \exp \left(-\frac{(z-\sigma )^2 \sqrt{\left(...
0
votes
0answers
10 views

Can a DNN learn the GCC-PHAT algorithm?

How would you create a DNN (and its training dataset) such that it is able to copy the GCC-PHAT algorithm?
0
votes
0answers
9 views

Signal/Wavelet Clustering

Problem Setting In an experiment: I have 3 signal sources and 10 sensors each generating wavelets as time goes by. The distances from each source to sensors change from experiment to experiment. ...
0
votes
0answers
10 views

Performance measure for estimation for acoustic impulse response

In searching for a performance measure for assert the estimation quality of acoustic impulse responses. Ideal Acoustic Impulse Responses (AIRs) are usually modelled as trains of impulses: $$ h(t) = \...
0
votes
0answers
5 views

Signal Embeddings using the skip-gram or CBOW model

So my work involves looking at a bunch of waveforms in the context of classifying events. I often am looking for new ways to represent my waveforms, and in my searching, I came across audio embeddings ...
0
votes
2answers
99 views

why is an MA process equivalent to a FIR filter?

John Cook claims that a FIR filter is equivalent to an MA process. But FIR filter is just a function of the previous inputs: $y_t = \phi(B)x_t$ and an MA process is a function of the previous ...
1
vote
0answers
32 views

Signal Decomposition

I have two time dependent signal sources X & Y. Both can be modeled as having a linear combination of time dependent individual components and common components; so X(t)=a(t)+C(t)+noise, Y(t)=b(t)+...
5
votes
1answer
84 views

Viral topics. How to describe and characterize bumps in time series of tag-activity on Meta Stack Exchange

Background There is much dissatisfaction on StackExchange. This can now be covered in over 250 questions on meta (see 1 and 2). In response to that I made a recent meta-post and supported it with the ...
2
votes
0answers
25 views

Detecting specific points in (noisy) dataset

In my recent work I've came across a problem where I need to find certain points in quickly oscillating data. Let's work with syntethic data instead of real measurements and ignore the noise for the ...
1
vote
1answer
36 views

How to discard the first spike after auto-correlation and handle sloping auto-correlation output [closed]

Disclaimer: I am not very mathematically inclined and am mostly looking to be pointed in the right direction. I have various signals that I am putting through an auto-correlation function that uses ...
0
votes
0answers
16 views

How to determine causal relationship between two temporal signals?

I have two noisy temporal 1D signals and knowledge that one drives the other, to some degree. You can see this because there are some temporary spikes in the first signal that (sometimes, if they're ...
0
votes
0answers
30 views

zero-lag filter: size of negative part of filter weights: when in-phase with sinusoid?

This question is about negative weights in causal filters and their effect on the lag, or "synchronization" with a sinusoidal signal. There are a few types of moving averages that use negative ...
0
votes
0answers
43 views

How to search for irregular signals: Fourier, DWT or k-means?

See my notebook here I want to search for irregular time signals in a data set of ~3 500 000 time signals. I can't give a clear definition of irregular signal, but it must fulfil the criteria of: not ...
1
vote
0answers
14 views

Cepstrum: quefrency scale to frequency scale

Can someone please explain to me how to convert a quefrency scale to the corresponding freqncy? For example consider this: A voice signal is measured at 50kHz sampling frequency and FFT power ...
6
votes
1answer
24 views

Can I use a LSTM Autoencoder to compute similarity between two variable-length audio signals?

I would like to compute the similarity between audio signals of different length. One way of doing it is to train a RNN (LSTM/GRU) Autoencoder and extract the hidden layer representation - feature ...
1
vote
1answer
41 views

Intuition of the convergence of sample ACF

One of the problems in Brockwell and Davis book about time series is to show that 1) if \begin{equation} x_t = a + b t \end{equation} then the sample autocorrelation ($\hat{\rho}(h)$) converges to ...
0
votes
0answers
49 views

Benefits of ML in signal processing

There is plenty of research on ML in signal processing. The majority of it, so it seams to me, is about showing feasibility of ML-based receivers (end-to-end or individual functional blocks of). To me,...
0
votes
0answers
42 views

Interpreting Normalized Cross Correlation

I'm having difficult understanding how to interpret a normalized cross correlation after using the function in Matlab for my research project. I've read through the Matlab help page and several other ...
0
votes
0answers
15 views

How to get audio stream from internal sound card and beat match using reinforcement learning

I'm working on a DJ project to play different tracks and mix between them. The approach I am following is that of tokui to use reinforcement learning to speed up or slow down a track so that tracks ...
0
votes
0answers
4 views

Compressed Sensing with a Non-Invertible Sparsifying Transform

In "The Restricted Isometry Property and Its Implications for Compressed Sensing" (https://statweb.stanford.edu/~candes/papers/RIP.pdf), Candes describes the Noisy Recovery problem to be as follows (...
0
votes
0answers
29 views

Signal to noise ratio for structural equation models

Consider the linear structural equation model with known $\beta$ as $$ SEM \quad X_k = \sum_{j=1}^{p}\beta_{jk}X_j + \epsilon_k$$ where $X_k$ is a random variable. I construct a data matrix $D_{m \...
0
votes
0answers
10 views

Defining error safety in cross correlation of two binary signals

I want to cross correlate two binary signals, where one is currupted by noise and shifted by a timeconstant tau, but has the same bit pattern (so basically an auto correlation). Similiar to case 2 in ...
1
vote
0answers
11 views

An Interesting Model with Unknown Orthogonal Design Matrix

Consider a linear mixed model, $$\mathbf{y}_{ij}=\mathbf{\Gamma}\mathbf{\mu}+\mathbf{z}_i+\mathbf{e}_{ij}, ~~ ~~i=1,\ldots,m,~~j=1,\ldots,n_i, $$ where $\mathbf{y}_{ij}$ are $k\times 1$ observation ...
0
votes
0answers
75 views

Estimation of NegEntropy

I am trying to evaluate the different ICA algorithms. To do that, one of the measure which I use, is to estimate the non-gaussianity using NegEntropy. I am trying to find a formula/function which can ...
0
votes
0answers
21 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 ...
0
votes
1answer
65 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" ...
0
votes
0answers
9 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,...
20
votes
4answers
6k 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 ...
0
votes
1answer
84 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 ...
0
votes
0answers
23 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 ...
0
votes
0answers
59 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 ...
0
votes
0answers
14 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 ...
0
votes
1answer
26 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 ...
0
votes
0answers
21 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, ...
0
votes
1answer
55 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 ...
0
votes
0answers
15 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 ...
2
votes
1answer
37 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 ...
0
votes
0answers
10 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^...
1
vote
0answers
23 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
2answers
165 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 ...
1
vote
0answers
37 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?
0
votes
0answers
39 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'...
2
votes
1answer
169 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
29 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
71 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
33 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
47 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
1answer
90 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
104 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 ...