Questions tagged [time-series]
The time-series tag has no usage guidance.
183
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Finding periodicity in discrete events II - missions to Mars
Per the Space Exploration SE question Are launch windows to Mars avoided if they result in landings during dust storm season? the synodic period of the relationship between the motion of Earth and ...
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3
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199
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How to align timeseries by decimating while preventing aliasing?
I have two pandas DataFrames, dfb and dfv, where dfb has a higher sampling rate than ...
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How to detect the end of a period of a repeating pattern in some time series signal
I have an incoming stream of time-series data which looks like in the below figure :-
I want to detect the end of each cycle in real-time (marked with red arrows) using C language. What would be the ...
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Best 'SNR-like' detection statistic for time series signal in the wavelet domain?
What is the best way to define a detection statistic for a time series event trigger generator, which computes the wavelet transform of some time series data? I want such quantity to be similar to a ...
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Do the first k elements of DFT (Xn) correspond to k lowest frequency components?
Do the result of DFT (Discrete Fourier Transform) of a 1D sequence order as low frequency to high frequency? and why is that?
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Discrete Time Signals - Time Scaling and Time Reversal
On the top graph, we can see a discrete-time signal $x[n]$.
I don't understand how for the signal $x[3-n]$, the impulses with magnitude $1$ still are at the positive indices $n = 1, 2, 3, 4$. Why ...
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25
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Resampling a signal with variable frequency [duplicate]
I haven't touched my signal processing courses for a long time and I forget how to work with these kinds of signals.
I have a signal that comes from a sensor that has 3 time periods.
The time vector ...
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58
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Random telegraphic noise and Lorentzian noise power spectral density
Following the example of the Lorentzian noise power spectral density shown above (ref), I would like to clarify the following:
In the first figure (labeled by (c)), May I please know why the constant ...
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101
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Construct complex signal from a real-valued time series and Hilbert transform
I have a time series measurement $v(t)$ from a physical nonlinear system and its power spectrum $E(f)$ look like the following
From a theoretical point of view, the solution of the system is modeled ...
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261
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In time series analysis, is taking a multi-period difference equivalent to a band-pass filter?
For time series, a simple high-pass filter is obtained by subtracting the previous value from each value:
$y(n) = x(n) - x(n-1)$
If I take a multi-period difference:
$y(n) = x(n) - x(n - a)$ where $a &...
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accelerometer data processing, time drift and fft
We have have a small data cleaning issue we would like to share.
Context: We have data from an accelerometer sensor worn at the hip. We set the device so that data are collected at a sampling rate of ...
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Online algorithm to detect non-directional volatility?
I'm trying to write an online algorithm to detect when a time series goes sideways (i.e., its mean trend or mean drift is approximately zero) but is also unusually volatile. For example, in the red ...
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108
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Algorithm to detect down-up-down pattern in time series
I'm trying to write an online algorithm in Python to detect this below Down-Up-Down pattern in time-series.
It's not hard to do roughly if I calculate 3 contiguous non-overlapping moving averages, and ...
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355
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How to generate time-series from a given one-sided PSD?
Generating time series from a given PSD has been discussed in this and some other forums already (which I've referred some of them below) but almost all of them are mostly descriptive and none of them ...
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How do I convert the Amplitude from Power/Amplitude spectral density?
I recently started working on PSD of seismic signals. PSD signal can be expressed in 2 ways. One in ($PSD=g^2/Hz$) and other in $PSD=((meter/sec.^2)^2/Hz)$ and $ASD = \sqrt(PSD)$.
More details have ...
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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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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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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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1
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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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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 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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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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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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326
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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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37
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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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235
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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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121
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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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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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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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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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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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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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275
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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