Questions tagged [time-series]

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2
votes
1answer
2k 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
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1answer
137 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
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1answer
615 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
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1answer
666 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 ...
4
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2answers
806 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+...
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3answers
247 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
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3answers
4k 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
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3answers
12k 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 ...
6
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3answers
5k 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
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1answer
383 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
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0answers
486 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
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0answers
84 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 ...
3
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2answers
2k 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
107 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
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1answer
434 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 ...
3
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1answer
2k 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
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1answer
186 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
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1answer
70 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....
2
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1answer
164 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
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0answers
64 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-...
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0answers
98 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
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1answer
54 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
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2answers
102 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
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1answer
346 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: ...
2
votes
1answer
135 views

Terminologies - lags, order in time series model

I am facing some difficulties with the terminologies - lag ($p$) and sequence length (number of data points) (N) used in time series model such as Moving average and Autoregressive model. Considering ...
0
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1answer
202 views

Time series forecasting on dsp embedded systems

I have a time series analysis algorithm that uses arima modeling and fits a model to the time series and gets the residual values. It is more of a statistical signal processing algorithm than a ...
2
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1answer
730 views

Predicting account balance based on historical data

Given the values of a bank account balance over time (see figure below as an example), how can one predict the account balance at a given date in the future ? Should I just fit one linear regression ...
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0answers
459 views

Finding lag times for multiple time series

I have $N$ time series which have unknown time offsets relative to each other. I want to estimate the $(N - 1)$ time offsets, $\tau_{i,i+1}$, which maximise the sum of the cross-correlations between ...
1
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1answer
919 views

fourier series fitting matlab

I am using cftool in Matlab to fit time series values to Fourier model with 8 terms: ...
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3answers
240 views

How do I know quantitatively if the correlation of two time series is significant?

I computed the correlation coefficient of two time series of daily observations, x and y, but noticed that the more sampling ...
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0answers
129 views

Any examples of analysis in time domain to extact information

I am sending a 20Khz signal from my phone and capturing all the signals while doing exercise above it. Here I have a signal of a person doing "hand scissors exercise" I am doing analysis on how many ...
0
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1answer
66 views

Should you include division by coefficient of variation in WV reconstruction for its normed 1D signal?

I make a new ECG time series from WV spectrum of original signal and its L2 energy normalisation. I am thinking if the reconstruction step benefits from covariance at each time point. I take later a ...
0
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1answer
449 views

Discrete time non-linear time invariant system dynamics descriptions (state-space or input-output relationship)

For the sake of simplicity the following notation $a_k := a[k]$ is assumed for time sequences. A completely general discrete-time (DT) non-linear(NL) time-invariant (TI) dynamical system can be ...
2
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1answer
90 views

Rollercoaster: determining subject position from inertial data?

I have inertial data (accelerometer, gyroscope, magnetometer) from phones of human subjects riding a single rollercoaster repeatedly. The ride has temporal variance (ex. sometimes getting from A to B ...
5
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1answer
4k views

Difference between Gaussian and moving average filters for peak detection and doppler shift detection?

Consider having a signal in the time domain, and you want to smooth the signal. Moving average and Gaussian filters that are used. How do you choose which is used for what? What are the conditions ...
2
votes
1answer
418 views

Help in interpreting the auto correlation graph

I want to check if a time series is (a) random (b) independent. For these I am using the autocorrelation (AC). Autocorrelation refers to the correlation of a time series with its own past and future ...
1
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1answer
53 views

Help with a product of a sum of infinite series [closed]

i would like some help with this: given: $$ h[n]=2^{-n} u[n] $$ calculate the series: $$ \sum_{r=- \infty }^ \infty h[n+4r] $$
1
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1answer
1k views

Adaptive Piecewise Constant Approximation (APCA) with wavelets/DWT

I am trying to approximate a vector or a time series, in order to have as little changes as possible. To do so, I pretend to apply the Adaptive piecewise constant approximation (APCA) algorithm. ...
1
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1answer
66 views

Good Reference Problem to Test Filtering/Estimation Algorithms

I am looking to figure out if a current filter algorithm I have built could be useful for some problems I am looking into at work. It isn't a Kalman filter, but is instead making estimations using a ...
1
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0answers
34 views

Unique signal extraction from a cumulated signal

I'd like to start off by saying that I am not very experienced at signal processing, so I apologise in advance if I do not explain everything properly the first time. I would like to analyse the ...
2
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1answer
1k views

Spikes in time series

I would like a simplified measure to quantify spikes in my time series, I have one series that has many and I would like to compare it to another that has very few. I have thought through several ...
0
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1answer
454 views

Periodogram frequencies not matching with signals

I am new to signal processing world. I am working on a project where we have to find change points using spectral densities. I am running some simulations where in I created a wave which is a linear ...
0
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1answer
272 views

Autocorrelation of a noisy linear map

I am interested in calculating the autocorrelation function of a linear map with some noise (model given below) but am slightly confused in doing so. At first, I did not realize there were two ...
1
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1answer
553 views

Delay issue in time series prediction

I am having an issue using neural networks to predict time series. Some predicted data fits with the expected data, as bellow: (In black the real time series and in blue the output of my neural ...
2
votes
1answer
202 views

How the noise in time series can be reduced?

I have asked the question in the following link: Are time series data always contain noise? I wonder if we could use variational methods to denoise the time series data just as in computer vision? ...
1
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2answers
184 views

Are time series data always contain noise?

I wonder if every time series data should contain noise or not. For example I am taking the price of a ticker, say Yahoo, every hour and noting the values. Does this data contains noise or not?
3
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2answers
6k views

Is R suitable for digital signal processing

While asking a question about representing large time series in R I was discouraged from using R for digital signal processing. I understand that R is geared towards statistics. However, a signal is ...
1
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0answers
65 views

Methods for edge detection with non-equidistant samples

This posting describes two methods of edge detection for wave analysis in a water pipe. I am not sure about advantaged and disadvantages. Therefore I want to evaluate the best method for this ...
5
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3answers
1k views

Estimate changing time lag between signals

Suppose I have two timeseries $x_1(t)$ and $x_2(t)$, shown in the image that I drew below. They look almost identical in general form, except some features are shifted slightly in time from one series ...
0
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0answers
45 views

How can I convert time-value pairs to a signal with a constant sampling frequency?

I have a time series consisting of [time, value] pairs. The series is ordered by time but the difference between two consequent times is not constant. For example: ...