Questions tagged [time-series]
The time-series tag has no usage guidance.
-1
votes
0answers
34 views
Time scale for the oscillation of a Gaussian random process
I have a Gaussian random process $W$ that's defined as the following:
$$W(t)=\sum_{i=1}^{n}\sin(\omega_it),\quad \omega_i\sim\mathcal U(\omega_a,\omega_b)$$
where $n$ is a large positive integer and ...
0
votes
0answers
38 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
13 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
9 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
64 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
79 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
78 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
39 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
41 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
72 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
24 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
70 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
13 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
124 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
273 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
34 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
230 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
votes
1answer
113 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
137 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
71 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
166 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
61 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
32 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
173 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
46 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$$
Then $\{X_t\}$ is a ...
2
votes
1answer
1k views
wavelet decomposition for time series signal
Is it possible to use stationary wavelet decomposition as a tool to extract wavelet features for a time series? I can see how it works for image cases, but for a time series prediction problem say $...
1
vote
1answer
99 views
Reproducing paper results about a wavelet transformation using python [closed]
I have been reading this PhD theis about wavelets and I am trying to reproduce some of the results but I don't know the specific code to use to generate similar results.
The original time series ...
0
votes
1answer
123 views
Find Amplitude of each period of time series
I would like to determine the of each period amplitude of a time series (e.g. the amplitude of each day). The time series has a constant period of 1 day and varies only in amplitude. I have tried ...
2
votes
1answer
206 views
Linear Predictive coding vs AR modeling
I'm looking for a suitable explanation of the circumstances in which the LPC error polynomial for a discrete time process x[n] is replaceable with an error polynomial categorized under the AR model? I ...
3
votes
2answers
141 views
Auto-correlation function, an inverse problem
$x[n]$ is a complex function $n=0,1,2,\cdots,L-1 $
we assume $x[n]$ is periodic in its index: $x[n+L]=x[n]$
Its auto-correlation function $C[n]$ is uniquely defined as:
$$
C[n]=\sum_{i=0}^{L-1} x[i+...
3
votes
3answers
136 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 ...
2
votes
3answers
897 views
What is the filter with the less phase shift?
I have to analyze a dynamic signal but there is too much noise so I applied low pass filter but then there is too much phase shift.So what is the most reactive filter I can apply to my signal ?
Best ...
1
vote
3answers
2k views
Window period(overlap) and FFT
How does changing the window period (i.e the number of points overlap between two frames) affect the FFT results ?
Suppose that a time series signal was converted to frequency domain by FFT with ...
3
votes
3answers
1k views
Need a better step detection algorithm
I have a time series with lots of steps/jumps (data file here). A plot is given below. I would like to subtract an appropriate value for each of these square wave features to bring them back down to ...
0
votes
1answer
207 views
Outlier Detection after Detrending a Time Series With Missing Values or NaN
Goal
Substitute outliers in a time series by most recent valid data
Problem
The time series (end-of-day stock prices) has several 'uncomfortable' properties:
It is non-stationary and can have ...
1
vote
0answers
191 views
Estimate standard deviation of random-walk using Kalman filter
I'm new to Kalman filters so this might be a stupid question.
I created a Kalman filter that takes in time series observations and estimates the mean of that time series. This is simply modeling a ...
3
votes
0answers
53 views
Minimum time delay that can be estimated between two sensors
Consider a 1-dimensional toy problem. I have two sensors at different points along the $x$-axis. Somewhere away from the sensors, a disturbance is created which travels towards the sensors, first ...
0
votes
2answers
626 views
How to Mesure the smoothness of a signal
so how can i determine if a signal is smooth or not ? And if its possible to get something indicating the level of the smoothness of my signal.
I looked at the r-squared and hurst exponent but i ...
2
votes
1answer
95 views
First Differentatior and Integrator
For discrete time series $Y$, first differentiation ($D_i=Y_i-Y_{i+1}$) and integrator ($S_i=Y_i+Y_{i+1}$) can be defined as two highpass and lowpass LTI digital filters. Where, transfer function for ...
1
vote
1answer
259 views
Pattern recognition in time series 4x3000 vector
I have a vector, here is a sample of some data from some heat flow data:
I would like to identify features in this image. In the example above I have identified one feature I would like to ...
0
votes
1answer
826 views
Show That the Power Spectrum Density Matrix Is Positive Semi Definite (PSD) Matrix
Given a Wide Sense Stationary Multi Variate (Vector) Random Process $ \boldsymbol{x} \left[ n \right] $ it Auto Covariance Matrix Function is given by:
$$ {R}_{x, x} \left[ m \right] = \mathbb{E} \...
1
vote
1answer
110 views
Comparing two time domain signals in a scale and shift-invariant way
I have two signals in the time domain, call them $S_1(t)$ and $S_2$(t). Because of calibration issues relating to the underlying devices that these signals are obtained from, they will not necessarily ...
0
votes
1answer
54 views
data analysis query
The hydrophone data is in analog-to-digital converter units. The 64000 sps data is 24 bits and the 375 ksps data is 16 bit.
The volts per bit conversion factor for the 24-bit channels is 1....
1
vote
1answer
70 views
Normalization of signal against reference
I am trying to figure out if there is any standard way of normalizing a sequence such as a time series against a reference sequence. I am not an expert on signal processing but I was hoping someone ...
1
vote
0answers
61 views
Auto-correlation of time signals [closed]
I'm interested in papers which are about auto-correlations of periodic time series signals.All relevant papers and applications are interesting to me, as I am studying the properties of the auto-...
1
vote
0answers
85 views
Why prediction by AR model causes time lag
Why does prediction by AR model cause a time lag?
Please tell me why theoretically.
1
vote
1answer
46 views
Index of stationarity of a time domain signal
During my internship, I've come across a software that calculates a percentage called "Index of stationarity". This index shows how much stationary is the signal. Does anyone have any idea on how to ...
1
vote
2answers
87 views
What is the type of these signals?
I want to do some DSP and Machine learning experiments on Electrical and Acoustic signals, but, due to some language setbacks, I didn't know how to call the type of my signal, what I use to google now,...
1
vote
1answer
132 views
Issue with the time vector returned by $\tt signal.spectrogram$ function
I'm puzzled by some very simple concept with building up a spectrogram.
Here is a toy example of the issue:
...
