Stack Exchange Network

Stack Exchange network consists of 174 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.

Visit Stack Exchange

Questions tagged [fourier-transform]

The Fourier transform decomposes a signal (a function of time) into frequencies, giving the energy at each frequency.

0
votes
0answers
16 views

About the power spectrum and confidence upper limit

For now, I have a coupled system with 5 variables and use the Runge-Kutta method to integrate. ...
0
votes
0answers
16 views

Significance testing of signal-to-noise ratio

I have three 18-second, 32-channel resting state EEG time series sampled at 500 Hz using dry EEG electrodes (condition 1) and three more 18-second, 32-channel resting state EEGs also sampled at 500 Hz ...
1
vote
0answers
31 views

Adaptive knot selection for B-spline fitting

When fitting a B-spline for regression purposes I've seen a lot of cases where knots are fixed uniformly ,but in some situations this could lead to poor estimations because the behaviour of the curve ...
2
votes
0answers
18 views

Non-linear regression. Obtain B.spline coefficients using Fourier Transform?

I came up with a idea to estimate the coefficients of a B-spline fit by using the Fourier Transform but I don't know if it makes any sense to estimate them in this way. Given that $$s(x)=\sum_kc(k)\...
0
votes
0answers
99 views

Characteristic function for a Chi-squared distribution

I would like to directly derive the probability density function (PDF) for a Chi-squared distribution with $k$ degrees of freedom using characteristic functions. If $X_{1}, X_{2}, \dots, X_{k}$ are ...
0
votes
0answers
16 views

Estimating Fourier parameters using least squar emethod

I'm given that $$ \sum_{t=1}^N \epsilon^2(t) = \sum_{t=1}^N\left[y(t) - \sum_{n=0}^{N/2}\left\{a_n\cos\left(\frac{2\pi nt}{N}\right) + b_n\sin\left(\frac{2\pi nt}{N}\right)\right\}\right]^2 $$ and ...
2
votes
0answers
29 views

How to fit a model to both daily and weekly periodic data using linear regression and fourier transform

I have a variable, y, in 30 minute intervals, and is highly dependent both on the time of day and the day of the week - mainly Sundays. It is also dependent on bank holidays, which could by any day of ...
0
votes
0answers
65 views

Forecasting seasonality with Fourier terms in R

I am using the auto.arima from the forecast package in R to determine the optimal K-terms for fourier series. After I do that, ...
1
vote
1answer
47 views

R forecast multiple seasonality optimal model search using fourier and msts objects

Hi I have hourly data (one obs one hour) with multiple seasonality. I would like to fit an ARIMA model using forecast R package taking into account the multiple seasonality, maybe taking also in ...
1
vote
0answers
149 views

Time Series Analysis: Fourier Transform [closed]

I've recently studied Fourier transform and I've applied it on a time series data, since I am still confused between time and frequency domain I doubt the authenticity of my code to calculate Fourier ...
1
vote
0answers
39 views

Fourier Output Meaning

I just ran a fourier series on weekly sales data for 3 years worth of data. I optimally chose the number of k-terms based on the AIC. First 6 lines of my data: ...
1
vote
0answers
20 views

RKHS norm and Fourier transform link

In the notes here, it is stated that norms of some reproducing kernel Hilbert spaces can be written in terms of Fourier transforms, and this is often used to argue that a higher RKHS norm implies a ...
1
vote
0answers
18 views

Is there a concept of weakly periodic in stats? If so, what is it called?

Ok, say we have a signal that reoccurs within every T+x time where T is a constant and x is a random number small in size compared to T. We know that a function is actually periodic if F(x) = F(x+T), ...
0
votes
0answers
36 views

How to generate synthetic data with specific spatiotemporal correlation

My dataset represents a field evolving over time, so has dimensions [X,Y,T]. I would like to generate synthetic data with the same autocorrelation structure and spatial correlations as the real data (...
0
votes
0answers
44 views

Need help understanding output of a periodogram

In my effort to understand the output of a periodogram I created a series (s) where 1,1,1,1,1,1,1,1,1,10 is repeated 100 times and then created a periodogram of this series using the following R code: ...
0
votes
1answer
168 views

Discrete Fourier transform of an exponential decay

I have a vector with an exponential decay signal, using Numpy: t=np.arange(128) a=0.1 decay=np.exp(-a*t) I would like to compute the discrete Fourier transform (...
0
votes
1answer
770 views

Forecasting with ARIMA ( Training and Test Data split)

I have an hourly time series of the average parking occupancy with data available from September 2017 up until June 2018. I would like to use the ARIMA model with external regressors to produce a ...
4
votes
0answers
140 views

Fourier transform of a Gaussian process

I would like to discuss and ask a question regarding the Fourier transform of a Gaussian process, if it makes sense. For that purpose, let me describe the following situation. Let $z(s)$ be a ...
2
votes
1answer
86 views

Sampling from characteristic/moment generating function

Suppose I am given a probability distribution only via its characteristic or moment generating function and I want to sample from that distribution to generate paths in a Monte Carlo simulation. Is ...
0
votes
0answers
20 views

Finding common trends in time-series

I have a 10 relatively noisy time-series. I want to check if there are any similar trends in the 10 sets. My simple way of initially looking would just be to cross-correlate each time-series with ...
0
votes
0answers
68 views

Applications of FFT algorithm in statistics? [duplicate]

Are there any applications of the FFT algorithm in basic statistics i.e.: estimating a density distribution? I would like to learn more about it - and it would be nice to work on an actual example ...
0
votes
0answers
18 views

Fourier Transform based imputation

Fourier Transform based imputation Can any body please assist me in understanding the Fourier Transform based imputation algorithm shown in Figure. I am struggling to understand ts and te. Link of ...
0
votes
0answers
19 views

How does the variance of a simulated Gaussian random field scale with the number of terms in the Fourier decomposition?

I numerically simulated a Gaussian random field and am trying to verify that the program is working correctly. One way is to check the variance of the result vs. the theoretical prediction. However I'...
2
votes
0answers
23 views

Linear regression on circulant matrices

I am reading the paper on High-Speed Tracking with Kernelized Correlation Filters and I am a bit stuck on the equivalence of Ridge regression in the frequency domain. Minimizing the typical equation ...
0
votes
0answers
96 views

How to interpret the Output of the following ARIMA model

How to interpret the output of the below ARIMA(with Fourier Terms) code y <- msts(ts(dataAR$Total[57:331]), seasonal.periods=c(30.4375,91.3125)) Model ...
2
votes
0answers
41 views

Time series/ ARMA Simulation

Given: I have a question, given a continuous real spectral density f(w), -infinity my idea: I would folding, discretize and truncate the spectral density to get a real (one-sided) discrete spectral ...
0
votes
0answers
25 views

Standardization of cyclical features for Clustering

I am about to start a project in data mining sales data using the well-known algorithm, t-SNE. Specifically, I have 4 millions of observations and 75 attributes for every sale. A graphical example ...
0
votes
0answers
123 views

FFT machine learning model for different rotation speeds

I am working on a machine learning model, that can classify different failure patterns of a rotating machine / motor based on a supervised approach. My features for the model are based on the ...
0
votes
1answer
154 views

Calculating right values of Periodogram using Fourier Analysis

In the book, Economic Cycles: There Law and Cause By Henry Ludwell Moore, he plots Periodogram of rainfall of Ohio valley. He uses 72 years data (1839-1910) and tries to find the most dominant cycle ...
1
vote
1answer
335 views

tbats() model not capturing seasonality (weekly data)

I have below 4 years of weekly data which has complex seasonality of varying seasonal length. 1) My first question is what should be the correct assigned frequency for this series (frequency() comes ...
0
votes
0answers
23 views

Full frequency space description of a continuous-time random process (e.g. signal) in

I don't know if signal processing or math would be a better forum, but I'll start here. Consider an ensemble of stationary random processes $x(t)$ that has the following properties: The PDF is $P[x]$...
3
votes
1answer
335 views

Proof of Herglotz Theorem in Time Series Analysis

I am studying time series, following Time Series Theory and Methods by Brockwell and Davis. I am reading the proof of the Herglotz Theorem, I have the following questions. First, the proof given in ...
3
votes
0answers
128 views

Kernel density estimation with FFT for a univariate non-parametric regression

The non-parametric regression model to be estimated looks like the following x_t = b(x_t-1) + epsilon_t Forfinding the optimal bandwith h in the kernel ...
1
vote
1answer
70 views

Spectral density and Riemann Stieltjes Integral

I am confused with a part about spectral densities. I found it in Time Series Theory and Methods by Brockwell and Davis. I don´t understand how is applied the Riemann Stieltjes Integral in this ...
0
votes
2answers
114 views

Is this a well-studied problem? Problem: Optimally unlagging multiple time-series

Is the problem of optimally lagging/unlagging multiple time-series with integer lags to maximize a sum of pairs of cross correlations or coherence an already well-studied problem? If so, references? ...
1
vote
2answers
138 views

Power spectral density of the output of a linear time invariant system with a weakly-stationary process

Please note that I have no background whatsoever in Fourier analysis and very little in time series. This is exercise 2.10 in Theodoridis' Machine Learning: Show that the autocorrelation of the ...
1
vote
3answers
1k views

Spectral Analysis in R - the periodogram

I am doing a spectral analysis in R using the spec.pgram() function. Suppose I have observations for $y_1$ to $y_n$ which are a time series with annual observations....
9
votes
1answer
279 views

Why are random Fourier features non-negative?

Random Fourier features provide approximations to kernel functions. They're used for various kernel methods, like SVMs and Gaussian processes. Today, I tried using the TensorFlow implementation and ...
0
votes
1answer
44 views

Generating time series for electricity demand

I'm working on a project, trying to model electricity consumption and generation from a bunch of PV generators to see how much of the demand can be satisfied by the production in the "town". Most ...
2
votes
0answers
239 views

How to define a loss function for discrete fourier series?

In each batch there are 8000 sample points, and I apply discrete Fourier transform on them. The original samples are real valued, so only the half of the result is needed. The end result is 4000 ...
3
votes
0answers
34 views

Representation of Noise in Fourier transform

I perform an experiment where I sample $M(k)$ which is in theory related to $|f(x)|^2$ via $M(k)=\int e^{ikx}|f(x)|^2\,dx$. I perform the discrete FT on my data in order to obtain $|f(x)|^2$. Without ...
1
vote
2answers
1k views

Dealing with multi seasonality in time series

I am new in R and time series analysis and need some help. I am currently trying to create a tool to forecast the demand of power for a company. On my data set I have 17550 observations that ...
2
votes
1answer
636 views

Finding out frequency of peaks using the Fourier transform

I have a signal that varies in time as shown below. I have just shown a 5 s interval of data (from 97 s to 102 s). The sampling frequency is 1000 Hz. My goal is to find out the frequency of the ...
1
vote
0answers
36 views

Comparing power in FFT frequencies biased by number of bins?

I have some EEG data recorded from a mouse with tremor. When I do an FFT on the data, it generally looks like an exponential distribution. I'm interested in any frequency peaks that are ...
1
vote
0answers
40 views

How to measure a mean frequence of fft transform

I have this time series (utilization of app by day of an user) And this fourier transform of the above time series How can I extract one number that express the mean frequency of this time series? ...
1
vote
0answers
73 views

Regression for Analysing Fourier Transform of a Complex Function

Regression for Analysing Fourier Transform of a Complex Function I need to analyse a linear system which is y = FT{x}, where Input x and output y are both complex function (A*exp(jθ)). If I only ...
0
votes
0answers
213 views

FFT as feature for neural network

i am trying to make a classifier that determines whether the audio sample provided is a girl or a boy. however i am only getting 50% accuracy on my classifer at the moment. I want to know if its the ...
1
vote
1answer
186 views

Energy savings prediction model using stochastic processes and Monte Carlo Simulation

I want to build a model that quantifies the energy savings from a building retrofit project. For example a company is using a heating oil radiator system, that is meant to be replaced by a gas ...
1
vote
0answers
140 views

detecting change point in the time series on a 2 dimensional space

I have a 2 dimensional geographic space. There are crime events occuring at different regions in the space over time. I am looking particularly at property crimes like burglary. If I look at the time ...
1
vote
0answers
484 views

Get the amplitude of the components of a periodic signal from Fourier (FFT)/Wavelets analysis

I have a signal looking approximatively as the one in the first subplot below (*), and I would like to: extract the periods of the main components of the signal; associate an amplitude to these ...