Questions tagged [time-series]

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For continuous systems that in Quasi-static / Static Equilibrium are Memoryless?

A. BACKGROUND: Apparently this question’s answer says this some static systems have memory especially those that hysteresis: Confusion about 'memoryless' meaning So the word static to me ...
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PSD to FFT for audio [duplicate]

I'm trying to convert a noisy input to fft and extract the signal using a local average. By the way, after the transformation of fft, it was found that the values of adjacent times of the same ...
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1 vote
1 answer
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Standardizing signals from the same experiment setup with different recording tools

I've been looking to merge two datasets I have, that capture instances of the same phenomenon using two different recording tools. Both are multichannel electrical signals, but the recording tools ...
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-1 votes
1 answer
37 views

Deterministic process, what is it ? how can i get a better intuition for it?

so I was following this code where the author cleans the data for a time series problem. He does some feature engineering , all is well and good until he does this ...
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0 votes
1 answer
46 views

Understanding shifts and superpositions in vibration sensor data

I’m looking at some measurements for elevator door vibrations from this dataset (a cleaned version of what is available here, as I understand it) and, if I plot the series of measurements, I get the ...
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0 votes
1 answer
62 views

How to determine multiple Periodicities present in Timeseries data?

My objective is to detect all kinds of seasonalities and their time periods that are present in a timeseries waveform. I'm currently using the following dataset: https://www.kaggle.com/rakannimer/air-...
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How to determine the area for the coefficients of an AR model to be asymptotically stable?

I am pretty new to this topic, and I am a little confused about the definition of asymptotically stable. If I have an AR model as follows $$y(t)=a_1y(t-1)+a_2y(t-2)+e(t)$$ How to define the area in ...
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1 vote
0 answers
42 views

How to restore time domain signal after multiply cosine signal when cosine signal has unknown initial phase?

I use AD9954 as cosine signal generator,then use ad835 to multiply this cosine signal with antenna signal. As ,the antenna signal frequency shifted after ad835,then ...
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2 votes
1 answer
97 views

difference in the spectral densities of autoregressive sequence by FFT and analytical solution

I want to obtain the power spectral density (PSD) of an autoregressive sequence, AR(1). The analytical solution according to this reference (page 12) is For $X_t = \phi_1X_{t-1}+W_t, W_t \sim N(0,\...
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correct fourier transform of time series starting with different start/end times

I have lots of time series where I want to analyse some periodic signal that occurs beside the signal I wanted to measure (and I didn't expect). The idea is that there's always a peak at a certain ...
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65 views

Should I use IQ data or power data to compare 2 signals through `similaritymeasures.dtw`?

I choose similaritymeasures.dtw to compare experiment signal exp_sig and reference signal ref_sig. Both signals are I,Q data ...
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Discrete Wavelet Transform: x-axis differences between python and MATLAB

This might be simimlar to the question: Why is there an amplitude difference in Matlab and Python?. But with the difference that I am focusing on the x-axis. To do a 5th-level decomposition, the used ...
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1 vote
1 answer
56 views

Pywavelets applied to time series

I'm new on this field. I am applying a discrete wavelet decomposition to a timeseries and the decomposition yields subsets of the data, specifically the half. Nothing wrong with that since that is the ...
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0 votes
0 answers
28 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 ...
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2 votes
1 answer
120 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,\...
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1 vote
1 answer
70 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}\...
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4 votes
1 answer
149 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. My goal is to represent it in the frequency ...
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1 vote
3 answers
105 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. ...
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4 votes
1 answer
185 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 ...
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0 answers
25 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 ...
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1 vote
0 answers
75 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 ...
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2 votes
1 answer
134 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 ...
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3 votes
1 answer
84 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 ...
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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. ...
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0 votes
1 answer
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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 ...
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2 votes
1 answer
193 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: ...
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1 answer
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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 ...
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32 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: ...
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1 vote
0 answers
73 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 ...
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0 votes
0 answers
69 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 ...
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0 votes
1 answer
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 ...
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0 answers
10 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 (...
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2 votes
2 answers
56 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 ...
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0 votes
2 answers
75 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. ...
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0 votes
0 answers
12 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). ...
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1 vote
1 answer
29 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 ...
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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?
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0 answers
43 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 ...
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0 votes
1 answer
45 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 ...
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1 vote
1 answer
108 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 ...
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0 votes
1 answer
52 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 ...
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0 answers
24 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 ...
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0 votes
2 answers
505 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 ...
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3 answers
56 views

How to find the interval peirod from a series of discreate time (numbers)?

I have a series of time, they look like this: ...
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3 votes
0 answers
66 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 ...
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0 votes
0 answers
25 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 ...
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1 vote
0 answers
29 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 ...
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0 votes
2 answers
74 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 ...
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1 vote
0 answers
21 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 ...
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1 answer
186 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 ...
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