Questions tagged [time-series]

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How to use Discrete Wavelet Decomposition for Time Series Forecast?

I'm very interested in using wavelet decomposition via filter banks to time series forecasting. There are several papers (1, 2, 3) where they uses a wavelet decomposition approach. Some of the ...
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1 answer
43 views

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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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 ...
2 votes
0 answers
34 views

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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1 answer
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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 ...
2 votes
1 answer
252 views

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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1 answer
43 views

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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3 answers
101 views

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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1 answer
180 views

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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2 votes
2 answers
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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
35 views

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 ...
-1 votes
1 answer
62 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 ...
1 vote
1 answer
65 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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1 answer
89 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 ...
1 vote
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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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1 answer
102 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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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 ...
1 vote
1 answer
178 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 answers
31 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 ...
2 votes
1 answer
169 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 answer
100 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
151 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 ...
1 vote
3 answers
215 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
585 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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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
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108 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
1 answer
215 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
379 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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1 answer
152 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
1 answer
298 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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1 vote
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94 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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96 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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1 answer
33 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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2 votes
2 answers
57 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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2 answers
156 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. ...
1 vote
1 answer
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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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1 answer
46 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
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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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1 answer
61 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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2 answers
687 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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