Questions tagged [time-series]
The time-series tag has no usage guidance.
103
questions
0
votes
0answers
20 views
decouple signal from environmental effect
Sensor signal depends on environmental factors such as temperature, relative humidity. Temperature compensation is relatively straightforward. But I am not entirely sure how to model the effect of ...
0
votes
1answer
32 views
estimation of ARMA(1,1) with MA parameter greater than 1
I am working with the following simple ARMA(1,1) model:
$$
z_{t+1} = \phi z_{t} + \theta\varepsilon_{t} + \varepsilon_{t+1}
$$
In my case $\theta$ depends on some other parameters, and, therefore, I ...
2
votes
1answer
186 views
Statistic that is responsive to changes in time series, yet not too volatile
Let's say I have a fairly volatile time series $X_t$ - it doesn't have any reason to show an upward / downward trend, but it does show drops and spikes from time to time. It can also change level (e.g....
2
votes
0answers
36 views
Relating Fourier and power-law descriptions of noise
I'm trying to understand this PDF, which is in English but has Polish authors, so there may be translation issues confusing me. The subject is the frequencies of sentence lengths in novels.
Eq. (1), ...
0
votes
0answers
18 views
How to correct for “track jumping” for multi-lined time series
I am creating an algorithm that tries to estimate three time-series that should not cross each other (voice formants). The problem is sometimes the algorithm mistakes one time series with another and ...
0
votes
3answers
62 views
Is $x[n]=(-1)^{n^2}$ periodic?
Is $x[n]=(-1)^{n^2}$ periodic? The answer said no, but when I draw it on a graph, it seems to be periodic, with fundamental period equal to $2$.
0
votes
1answer
48 views
How to compare and measure the similarity between two between two signals?
I'm working on different sensors data, the question is this: I have two signals (coming from two different sensors measuring two different phisical charactheristcs of the same "object").
I know for a ...
0
votes
1answer
33 views
Test for Equivalence of two time series
I wish to test whether two time series are equal. So I believe best way to define equivalence is that given two time series, say $\{x1_t\}$ and $\{x2_t\}$, we show that both the series come from the ...
1
vote
1answer
47 views
How to determine the phase of a time-sampled periodic signal?
I know this is a rather common and a rather simple problem, but somehow I can't find a solution that is equally simple to understand (and implement).
I have a signal that closely resembles a noisy ...
0
votes
0answers
15 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. By eyeballing I have found hundreds of flat and oscillating signals, but just a few that are ...
0
votes
0answers
27 views
How can I relate my amplitude from a FTT to the actual signal?
Sorry for disturb you guys, I've been playing with this the last days. I am computing signals of a wave produced with a wavemaker. Cause I have several sensors (wave gauges) I am sensing the same wave ...
1
vote
0answers
20 views
Wignerville of market data [closed]
I am trying to get some insight into market data, in this case the stock KO. Here is the chart:
If I take the wignerville of ...
1
vote
0answers
102 views
SNR computation in frequency domain with scipy.fftpack.fft
I have a noisy time series (gaussian coloured noise) to which I add a signal. I call the sum of noise+signal a segment. In the picture you can see an instance:
I want to compute the signal-to-noise ...
0
votes
1answer
79 views
How to group similar patterns together that are shifted along the x axis?
I have a set of time series plots that are shifted along the x-axis. I am looking for an algorithm using which I can group them together. My end goal is to average them.
While reviewing the ...
0
votes
2answers
355 views
How would you use machine learning for peak detection?
I have a noisy signal and I'm trying to find a way to detect peaks with ML. The "peaks" are easy to find as human because they are rhythmic and have the same "general" shape but the amplitude and ...
-1
votes
1answer
38 views
How do I obtain the fourier series coefficients for a signal obtained by multiplication of two signals of different frequency?
What i assume here is that LCM of time periods of the two taken signals exist that is signals periods are not like pi/2 and 1 but are rather like 1 and 2 (just an example)
I am given fourier series ...
0
votes
0answers
7 views
How to normalize data by mapping data points from one mixture of multivariate normal distributions to another
Problem description
I am trying to normalize multivariate time series data. The individual
data sets (spectrograms from temporal EEG) comes from sources that differ widely in their noise ...
0
votes
0answers
17 views
Bank Filter over a 1D signal
I would like to apply a filter bank decomposition over a time series signal.
If I am correct, it is necessary to take a low pass and a high pass filter, and then convolve them with the time series.
...
0
votes
0answers
15 views
Matlab time serie mat file format
I'm trying to find the ideal data exchange format for our signal processing data. I've tried various formats like csv, wav (unsuitable), UFF, tdms, but there always seems to be some guy saying "don't ...
0
votes
0answers
52 views
Negative Exponential Filter SciPy
I'm trying to transform a time series with a recursive filter to model a feedback.
I was able to do a simple filter like :
...
0
votes
0answers
7 views
After fitting auto ARIMA's order, in prediction I'm getting bad result
For sunspot dataset.
Below is the ARIMA code. Auto ARIMA finds the best ARMA(2,1,2)(2,0,1) model. But when I plot the prediction seems wrong:
...
1
vote
0answers
15 views
Gray Level Dependence Matrix applied to time domain signals
It make sense to calculate gray level dependend matrix on al time domain signal in order to extract features related to that matrix?
I have EEG signals from stroke people in the time domain. My goal ...
0
votes
0answers
14 views
How to match resolution of two or more signals
I have received the following 4 time-series signals and wanted to do some data analytics using these. Although the sampling is the same for all of these signals, 2 samples per second, problem is that ...
1
vote
1answer
107 views
Amplitude and Phase of FFT gives messy results - Matlab [closed]
I'm trying to calculate the spectrum magnitude and phase of a signal, but when I plot them I get pretty messy results:
The signal is displayed on the right, then I have the magnitude and phase of ...
0
votes
0answers
214 views
Using Wavelet Transform on a 1D signal while updating the values
I'm working on a NN that uses Wavlet Transformed signals (with different wavelets and levels) and combines them with an additional Statistical Features input (input_4) to provide one step ahead ...
2
votes
3answers
153 views
Causal unstable system turn into stable anticausal?
I would appreciate it very much if someone would be able to provide some clarity, help or comment on this problem.
I have been reading several papers on time series identification such as
https://www....
0
votes
1answer
89 views
Fourier Transforms, symmetry, real/imaginary
I was hoping to clarify if the following was correct:
-a real function (neither even nor odd) in time exhibits conjugate symmetry in frequency, so the real part of the frequency response is even, and ...
0
votes
0answers
95 views
How to compute the energy of a time series?
I am analyzing the vertical component of 1Hz sampled geomagnetic data. These data were band-passed filtered around 0.01Hz (100s).
I would like to compute the daily energy contained in these time ...
1
vote
1answer
177 views
Filtering and peak finding
I have an observed signal which is the norm of the sum of two 3-vectors:
$$
S(t) = || \mathbf{A}(t) + \mathbf{B}(t) ||
$$
Now, I have full knowledge of the vector $\mathbf{A}(t)$,
$$
\mathbf{A}(t) = \...
0
votes
0answers
26 views
How to detect & eliminate the initial lag that occurs in time series data
I am working with vehicle data. In order to better study the system and I am looking for a automated tool that can delete the initial lag where no work function takes place. It'll be great if someone ...
2
votes
1answer
75 views
Simulate time series given temporal auto-correlation functions
Given a random process $x[n] \in \mathbb{R}$ (say of length $N$) and all correlation functions such as:
\begin{align}
\langle x[i]\rangle\\
\langle x[i]x[j]\rangle\\
\langle x[i]x[j]x[k]\rangle\\
\...
1
vote
0answers
16 views
How would PCA run on multivariate time-series data affect phase relationships across variables?
I am running PCA on a multivariate time-series dataset using observations across time (i.e. w/out time as an explicit variable) as the design matrix. Given this setup, I've found that it is difficult ...
0
votes
1answer
233 views
Detrend data with no clear secular trend prior to Fourier analysis?
I am completing Fourier analysis on many different time series of sediment particle flux exiting an experimental flume. Data is collected at a resolution of 1 Hz for durations ranging from ~5,000 to ...
2
votes
1answer
853 views
Comparing multiple signals for similarity
I have multiple (between 2 and 100) signals and need to determine when a significant number diverge from the rest. We're exploring machine learning techniques, but we also want tackle this as a signal ...
0
votes
0answers
40 views
About the power spectrum and confidence upper limit of a time-series data
For now, I have a coupled system with 5 variables and use the Runge-Kutta method to integrate.
...
2
votes
1answer
679 views
How to make a Power Spectral Density Plot in R
I have a time series point process representing neuron spikes. I have computed and plotted autocovariance using acf but now I need to plot the Power Spectral ...
1
vote
1answer
284 views
How to find correlation/cross-correlation of two signals in real time?
Considering there are two signals and the signals are real time in nature. Visibly when one signal does up the other signal does down and vice versa. Sometimes both the signals moved towards the same ...
0
votes
1answer
211 views
How good or bad my downsampled data is?
Suppose I have time series data at a one-minute resolution. Now I downsample data by taking mean of every 10-minute window, i.e., after downsampling, 60 readings will reduce to 6 readings. How should ...
1
vote
0answers
92 views
How to estimate noise by eigendecomposition of the variance covariance matrix?
I'm new here so I will try to be as clear as possible.
I am trying to apply some techniques from signal processing framework to denoise financial time series.
I would like to know if what I am ...
0
votes
2answers
273 views
Identify random repetitive patterns
Forgive me if it’s too basic, I finish engineering a while ago.
Given any time series, not periodic, I would like to find any repetitive pattern that is distinct (by some given measurement) and is ...
0
votes
1answer
90 views
How to programmatically find a sharp change in slope
First, apologies if I have the wrong group or this question is far too easy for this group. I am (as you'll see) a newbie. Please point me to another, more appropriate group OR tell me how to fix the ...
0
votes
1answer
36 views
Question on Levinson's proposed discrete form of Wiener filter
The whole foundation of Levinson's discrete version of Wiener filter is based on the assumption of stationarity of a time series, and aims to predict a value based on the past observed values. Now, if ...
2
votes
1answer
270 views
How to reduce latency under mean filter for high noise?
We have a position sensor that under some conditions receives some high frequency noise. We can eliminate that very well with a simple mean filtering.
Unfortunately this causes too much lag when ...
0
votes
1answer
63 views
Why doesn't law of large numbers apply to this stationary time-series?
There's a paragraph in Wikipedia that states the following:
Let Y be any scalar random variable, and define a time-series $\{X_t\}$, by
$$X_{t}=Y\qquad {\text{ for all }}t$$
Then $\{X_t\}$ is a ...
2
votes
1answer
1k views
wavelet decomposition for time series signal
Is it possible to use stationary wavelet decomposition as a tool to extract wavelet features for a time series? I can see how it works for image cases, but for a time series prediction problem say $...
1
vote
1answer
109 views
Reproducing paper results about a wavelet transformation using python [closed]
I have been reading this PhD theis about wavelets and I am trying to reproduce some of the results but I don't know the specific code to use to generate similar results.
The original time series ...
0
votes
1answer
241 views
Find Amplitude of each period of time series
I would like to determine the of each period amplitude of a time series (e.g. the amplitude of each day). The time series has a constant period of 1 day and varies only in amplitude. I have tried ...
2
votes
1answer
294 views
Linear Predictive coding vs AR modeling
I'm looking for a suitable explanation of the circumstances in which the LPC error polynomial for a discrete time process x[n] is replaceable with an error polynomial categorized under the AR model? I ...
3
votes
2answers
203 views
Auto-correlation function, an inverse problem
$x[n]$ is a complex function $n=0,1,2,\cdots,L-1 $
we assume $x[n]$ is periodic in its index: $x[n+L]=x[n]$
Its auto-correlation function $C[n]$ is uniquely defined as:
$$
C[n]=\sum_{i=0}^{L-1} x[i+...
3
votes
3answers
160 views
Extracting common signal without knowledge about noise [closed]
Given two noisy time series thought to contain a common signal,
$$ x_1(t) = s(t) + n_1(t), \quad x_2(t) = s(t) + n_2(t), $$
what is the best way to determine $s(t)$ without assuming any distribution ...
