Questions tagged [time-series]
The time-series tag has no usage guidance.
167
questions
0
votes
0answers
20 views
pattern recognition with some features in time series data
I am trying to capture peaks in a time series data which has some predefined feature.
Here is a snapshot of time-series data (Time series data with peaks)
In this time-series I want to detect peaks ...
1
vote
1answer
57 views
Impulse response of Time Varying Channel
I have just started studying LTV channels in wireless communication.
I know that $y(t) = \int _{-\infty} ^\infty x(t-\tau)h(t,\tau)d\tau$ Is there any way we can calculate the Impulse response $h(t,\...
1
vote
1answer
36 views
Time Shifting, Reversal and Delay
For a signal, $s(t)$ undergoing multiple transformations of time scaling, reversal and delay, how should I approach the problem of finding the resultant output signal?
$$s\left(\pm \frac{t-t_0}{T}\...
3
votes
0answers
36 views
Frequency representation of relaxation processes
I simulated a discrete sample of a variable whose autocorrelation function (ACF) should theoretically be composed of a sum of exponential-like functions.
I want to represent it in the frequency domain ...
1
vote
3answers
84 views
Convert a list of values and times into an audio file
I have two pandas dataframe, one with time in seconds and one with the actual audio data (values from -1 to 1).
The audio data points are not equidistant, this why I need the list of time in seconds.
...
4
votes
1answer
47 views
How to automatically identify the start and stop times of a "ramp" seen in time series?
I am analyzing pressure data sampled at 1Hz. The times series exhibit "ramps" (a linear increase in pressure followed by a sudden drop) for which I would like to automatically detect the ...
0
votes
0answers
23 views
Signal filtering with physical limitations and estimated STD
I have a prediction mechanism that predicts some signal value. Generally the prediction look like this:
The are some ranges of systematic error and I cannot do anything with this. But in many points ...
1
vote
0answers
33 views
Zero phase - Minimum phase of Butterworth filter [closed]
I am trying to implement the Zero phase - Minimum phase of Butterworth filter (1st, 2nd, and 3rd order) from scratch using python. Based on the resulting plots, it seems that I am doing something ...
2
votes
1answer
74 views
inverse fourier transform coefficients
Context
I want to implement (real) cepstrum on stock data (for example MSFT stock) and achieve cepstral coefficients of this time series.
as noted in "Cepstral-based clustering of financial time ...
3
votes
1answer
40 views
Synchronizing 2 time series signals at slightly different sampling frequencies
I'm working with an embedded system that has two acquisition channels and unfortunately, their clock crystals are slightly out of sync. Even though both boards are configured by software to sample at ...
0
votes
0answers
11 views
How to create an objective function for Mackey glass time series (using "bayesopt")?
I am optimizing 5 hyperparameters of Mackey-Glass time series and using built-in function "bayesopt" in MATLAB. My Mackey glass time series with fixed parameters shows correct results. ...
1
vote
1answer
31 views
Clustering FFT frequency bins from sensor time series data
I am trying to analyse multivariate time series data sets. I have 6 signals for each event, representing 3 linear accelerations and 3 rotational velocities for a 40ms window. I am trying to find a way ...
2
votes
1answer
99 views
How could I do a Discrete Fourier Transform in Python if my data is non uniform?
I have been trying to find a way to transform my time series data in an equivalent manner to the discrete Fourier transform. What I wish to find is something like:
...
0
votes
1answer
22 views
Estimating and applying lag smaller than time steps?
I have two time series with time steps of 1. I suspect there is some small lag between those two. I want to bridge that gap. And The lag is smaller than 1, so acf doesn't help.
Is there any technique ...
0
votes
0answers
26 views
2D space and 1D time evolution of a random field
I also asked this on math stack-exchange, but it is also relevant for the signal processing community.
I want to develop a 2D random field and its change with time with constant velocity. My process:
...
1
vote
0answers
51 views
How to remove noise from the signal? [closed]
I'm new to DSP and currently working on time-series data. The mentioned time series (of Toe) is extracted from a video tracking various body parts of an athlete. Ideally, there shouldn't be any ...
0
votes
0answers
39 views
Gabor uncertainty and time-frequency resolution
I have a question about Gabor's uncertainty theorem, and how it relates to time and frequency resolutions.
As I understand it, Gabor's uncertainty theorem states that the standard deviations of a ...
0
votes
1answer
32 views
n independent, normal, random variable distribution
There is 2 time-series signal and we have to compare the distribution of them.
I have heard there is a theory that says for n independent, normal, random variables of a series with many members, the ...
0
votes
0answers
9 views
Split Electroencephalogram data into interictal and preictal segments
I like to build a classifier to predict EEG seizures for my undergraduate work. I read that researchers tackle this as a binary classifier: interictal (normal behavior of the brain) vs preictal (...
2
votes
2answers
54 views
Methods for time series estimation in time domain
I am trying to estimate the clean form of a time series, $u(t)$ that is corrupted by additive White Gaussian noise $w(t)$ at a particular SNR. The received signal is:
$$y(t) = u(t) + w(t)$$
My first ...
0
votes
2answers
38 views
Can i represent a Time series signal as a spectogram image with desired shape
I am trying to represent sensor data in spectrogram form.
The data set consists of multiple 1D time series with a constant frequency of 1024 Hz taken from observations, cut into 1-minute sequences. ...
0
votes
0answers
11 views
Optimal fiducial marker design for signal registration
I have scalar, time series data being produced by a set of measurement devices. For simplicity, assume that all the devices operate at the same sampling frequency (I can always interpolate if not). ...
1
vote
1answer
25 views
Constrained interpolation/smoothing of multi-dimensional time series
Consider an $N$ dimensional time series $x_i(t),~i\in\{0,1,\cdots, N-1\}$ where $x_i(t)$ is smooth. It turns out that for all $t$: $x_i(t)>x_{i-1}(t)$.
The multi-dimensional series is sampled at ...
0
votes
0answers
32 views
Is it possibel to use CNN to bandpass signal?
I have a time serie dataset and want to train a CNN-LSTM model to predict as well as detect outliers. How can I use CNN to filter the signal and extract features from specific frequency band?
0
votes
0answers
37 views
Peak detection in noisy waveforms
I have a set of 1-dimensional time-series, a subset of which contain either one or two peaks, and the remainder of which are pure noise. I've smoothed these data by ...
0
votes
1answer
43 views
Different mathematical signal models for different applications
I am looking for some interesting and physically meaningful applications of different signal models. I am currently working with complex analytic signal model given below, but I couldn't come up with ...
1
vote
1answer
52 views
Is a continuous time aperiodic signal discrete in the time domain?
This is a statement I have read from a textbook:
Whenever we have periodic signals continuous or discrete time the frequency domain is discrete and time domain is continuous.
Whenever we have ...
0
votes
1answer
45 views
Calculating power of brain signals
I have a dataset that contains EEG (or MEG) recordings of brain signals during some cognitive tasks.
Each row, shows the source estimates of neurons in a particular region.
source estimate contains ...
0
votes
0answers
21 views
Correlation metric for time series with non-constant proportionality
I'm looking for a robust metric to express the similarity between two time series having the same behavior, as simplified below. When one increases, the other increases (same for decreasing or being ...
0
votes
2answers
288 views
Why does my amplitude change upon inverse Fourier Transform when I am only randomizing the phase of the fourier transform using Python numpy?
I am trying to make a surrogate time series of a discrete data series using python, basically I wish to keep the amplitude same and change the frequency
I take a Fourier Transform of the data
I ...
0
votes
3answers
55 views
How to find the interval peirod from a series of discreate time (numbers)?
I have a series of time, they look like this:
...
0
votes
0answers
9 views
Error in check.datum(x1) : biwavelet package R
I am using CWT through biwavelet package to generate results of the Continuous Wavelet Spectrum of a time series. I have 443 observations of the time series. I want ...
3
votes
0answers
49 views
Running window design for irregular or nonuniform time series
I have to deal with multiple time series $X_n$ that are non-uniformly or irregularly sampled at increasing times $\Theta=\{t_k\}_{k\in \mathbb{Z}}$ ($ t_k<t_{k+1}$). In case this could help, this ...
0
votes
0answers
8 views
Predicting the class of an event or its probability in n days after
I have a dataset with time series and for some of them (test sample) dates are known (maybe from zero to several pieces per time series), which we will call target events, the occurrence of which I ...
0
votes
0answers
23 views
How to interpret a break in linearity when performing detrended fluctuation analysis?
I have time series with 1048 values and when I perform detrended fluctuation analysis on this time series (using the windows or scales of 2^4 to ...
1
vote
0answers
23 views
Estimating Average HR from PPG sensor
I am reading Smartphone based Blood Pressure Monitoring via the Oscillometric Finger Pressing Method, which is trying to estimate blood pressure from a PPG sensor and a small applied force finger ...
0
votes
2answers
53 views
Power Spectral Density as a single number confusion
I'm trying to recreate the results of a machine learning applied to the DSP classification in the article: link.
I have a signal (activity measurements from a smartwatch) per patient, so about 30 ...
1
vote
0answers
19 views
How to select the ARMA model parameters?
I have a series of data containing 120,000 points. The mean of each N(=60) point is zero. I want to forecast the next 60 points using the ARMA model. My question is, specificaly, how to choose the ...
0
votes
1answer
138 views
problem with FFT in PYTHON
so,
I got a time series data. t = array (of regular interval starting from
0) length of t = n = 2080 dt = temporal spacing = 2.e-10 I have a set
of data at t values E(t) = array
Now, since I want to ...
0
votes
1answer
77 views
Comparing two Accelerometer signals in time domain
As a research to answer my question, I've been reading several posts on this stack with a common thread of "comparing signals". The methods recurrently suggested were to use DTW, correlation ...
0
votes
0answers
15 views
Calculate ACF in C++?
I would like to manually reproduce the method that authors of an article used in their research (DOI: 10.1038/s41598-017-02750-9 (Page 8. top)). It is mentioned as "ACF", so I wrote ...
0
votes
2answers
90 views
Processes/Transforms involved to get brainwave data from raw EEG? (Autocorrelation confusion)
Not clear on what the autocorrelation function of raw EEG means physically
why can't you take the FT of a the EEG itself and get frequency data?
With BCI & basic electrode setups you can ...
0
votes
0answers
12 views
Discrete Wavelet Transform Time Series
My problem is to cluster some time series together. But due to a huge length I was interested in using some methods to reduce the dimensionality. I was thinking of Discrete Wavelet Transform since the ...
1
vote
1answer
603 views
Python: Dynamic Time Warping, what actually is a 'similarity score' and how to compute it?
I want to compare two time-series data to see their similarity to each other.
For this task, I use Dynamic Time Warping (DTW) algorithm. I have tried the implementation using Python ...
2
votes
0answers
83 views
What is the physical significance of statistical quantities like mean, variance, skewness and kurtosis of a digital signal?
I understood the mathematical meanings of the mean, variance, skewness and kurtosis. But when we calculate these quantities for a signal (say a digital audio signal), what physical meaning do they ...
0
votes
0answers
27 views
Removing frequencies and reconstructing signal
I am trying to implement this section of this paper:
https://arxiv.org/abs/2012.15846
The rPPG signal is the spatial average of green value per frame over a video. Head orientation signals are a ...
0
votes
1answer
54 views
Good test for periodicity between signals
I have two timeseries signals. They look like this:
Each signal started out from the same array, but each received different preprocessing treatments. Ultimately, each signal represents the breathing ...
0
votes
1answer
153 views
Why does alpha of 0.5 in detrended fluctuation analysis indicate randomness?
I'm trying to get an intuitive understanding of the different coefficients in detrended fluctuation analysis (DFA).
It is used to detect fractal patterns in time series and it yields a coefficient, ...
0
votes
0answers
27 views
Periodogram of time series with multiple seasonal behaviors
I have a time series of sampled for every 5 minutes for 20 years of some geological signal. I would like to generate a periodogram in order to analyze what seasonal behavior affects the signal. At ...
3
votes
2answers
68 views
Help with denoising signal and periodogram analysis resources
This is a cross posting from the crossvalidated stack exchange as I thought this may be a better forum to ask.
I have a dataset consisting of respiratory time series signals of different lengths ...
