Questions tagged [fourier-transform]
The Fourier transform is a mathematical operation that decomposes a function into its constituent frequencies, known as a frequency spectrum.
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About Fourier transform of periodic signal
In Fourier transform for periodic signal, I checked different books and I found a different explanation in each book. Let's take the explanation in Signals and Systems by Rajeshwari & Rao:
The ...
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Derive Frequency Representation of Impulse Train Function
I want to walk through the derivation of the frequency representation of an impulse train.
The definition of the impulse train function with period $T$ and the frequency representation with sampling ...
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Why is `fftfilt` (i.e. `fft` of both inputs, then element-wise multiplication, then `ifft`) faster than direct convolution?
I have the following matlab code
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How Much Zero Padding Do We Need to Perform Filtering in the Fourier Domain?
Consider an $M\times N$ image $f$ and an $G \times K$ filter $h$. Given that convolution in the spatial domain corresponds to multiplication in the Fourier domain, then we can perform a convolution of ...
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What's the impact of aliasing in the time domain?
I've been studying digital audio and come across something I can't understand. There appears to be something like a consensus (among those capable of understanding such things) that the impact of ...
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Does sampling in the frequency domain cause time-domain aliasing?
Let's say I have an impulse response $h[n]$.
I analyze the power spectrum of that impulse response similar to fourier transformed $h[n]$ corresponding to roughly $H[f]$.
Now I compare $H[f]$ with ...
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Why can't DFT be used when samples are not equally spaced in time?
I found the following comment here
The DTFT can be used when the samples are not equally spaced in time, the DFT cannot
My initial thought was that this had to do with periodicity of the basis ...
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Difference Between Convolution and Multiplication [duplicate]
I read that multiplication is convolution in frequency domain. I also understand that convolution is just polynomial multiplication. Can somebody explain what are the advantages of doing convolution ...
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Calculating an image's fourier spectrum by hand?
Suppose I have a $4x4$ image with the following values as its grey-level intensity for each pixel like this:
I want to get its Fourier spectrum. Usually, I would just punch into Matlab and run a fft ...
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Fourier transform of given signal
This is the signal whose FT i need to find, at first i thought that i could solve this as a convolution of two rectangular pulses, but i could not find pulses that fit into this (it turns out that ...
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Why does the Fourier Transform of the impulse look so different from the Fourier Transform of the impulse train?
The fourier transform of the impulse functions is:
$$ \delta(t) \longleftrightarrow 1$$
The shifted delta:
$$ \delta(t-nT) \longleftrightarrow e^{-j \Omega nT}$$
But the fourier transform of the ...
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What will be the filtered output?
I tried to solve this question from basic
Here is my work
Image 1
Image 2
But the correct answer is Option $(B)$.What is the mistake i am doing?
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Which information do we get from magnitude and phase spectrum?
I am learning image processing. I want to ask very basic question related to FFT topic
Which information do we actually get from "phase spectrum" and "magnitude spectrum" about an image?
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Finding out modulation index and DC offset
I have a question form my teachers, and I cannot understand why I can find out the modulation index form the figure.
The question provide a Figure like this:
And the information signal is a ...
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Amplitude after Fourier transform
How to obtain the correct amplitude after the numerical Fourier transform of a signal?
Example: consider an exponential decaying wave $y(x)=e^{-x}\sin(100\pi x)$ with Fourier transform $y_f(x_f)$ ...
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Count Matches to a Kernel
So, I have this problem where I want to apply a kernel to an image and count the number of matches that happened.
So for example, if I have the kernel:
$$\begin{bmatrix}
1 & 2 & 1\\
1 & ...
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Can I assume system is LTI when given by DTFT of impulse response
I'm having hard time to grasp it probably because i don't fully understand it.
I understand that when a system is given by $h(t)$ (in general $h(t-\tau)$) i can assume that it is a LTI system.
So i ...
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The Number of Sine and Cosine Waves in an $ N $ Point DFT
This is bound to be an embarrassingly simple question, but here it goes...
I was reading the chapter on discrete Fourier transforms (DFT) of this really didactic online book, The Scientist and ...
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Does “keying on” a sine wave at a zero-crossing reduce its bandwidth?
I understand that a pure sine wave of infinite duration occupies no bandwidth, i.e. it is only the modulation of a carrier that gives it sidebands. Does the exact timing of a sudden modulation make ...
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DFT of discrete signals, why do we only analyze frequency bins equal to number of input samples?
If we have a signal $x[n]$ such that we have $N$ samples i.e. $n=0, \ldots, N-1$, then when we analyze the DFT $X[k]$ we only analyze for $k=0,\dots,N-1$ as well.
Why is the range of $k$ tied to the ...
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$2\pi$ periodicity of discrete-time Fourier transform
In my signals and systems course, we have learned that the discrete-time Fourier transform is $2\pi$ periodic, but the continuous-time Fourier transform is not periodic in general. For reference, we ...
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How does Adobe After Effects generate its “audio spectrum” effect?
I'm trying to replicate the "audio spectrum" effect from Adobe After Effects. An example can be seen in this video:
Obviously, it has to be some variant of a fourier transform, but I've tried taking ...
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Interpreting the inverse fourier transform from a graph
I'm given a graph of the fourier transform of some function $x(t)$. The graph is labelled $F(X(\frac{\omega}{\pi}))$ on the y-axis and $\frac{\omega}{\pi}$ on the x-axis. The graph is plotted only ...
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Implementation of wideband beamformer for planar array
I would like to obtain a good reference (or references) on the implementation of a wideband beamformer for a small planar (rectangular) array comprised of 4 rows by 6 columns, for 24 elements in total....
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Whats the optimal window function to use for analyzing real-time data samples?
Say you wanted to run a X point FFT on the last X audio samples that were played. The problem being, using a normal hann window function would place emphasis on the "middle" of the audio sample. ...
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Intuition behind image derivative using Fourier Transform for edges detection
This equation can be shown mathematically:
$\frac{\partial f}{\partial x}=\frac{2\pi i}{N} \mathcal F^{-1}\left(u\cdot \mathcal F(f(x,y)\right)$
I am struggling to understand the intuition behind it ...
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Why edge sharpening produces high frequency?
I have a low-resolution image in which the high frequencies are missing. When I apply an edge sharpening filter some of the missed high frequency is recovered.
I am wondering why this edge sharpening ...
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What is difference between terms $X(j \omega) ,X(\ e^{j \omega })$ and $ X(\omega)$?
While studying frequency transforms ,I get confused with the terms like $X(j \omega) ,X(\ e^{j \omega })$ and $ X(\omega)$
,where $ \omega = 2 \pi f $.
So what is the difference between them ?
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A kind of Phase Retrieval problem
I know there are lots of papers proposing algorithms for the problem of reconstructing a signal from modulus of its Fourier Transform (so-called Phase Retrieval Problem).
Also, recently it is studied ...
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Signal Processing using Fourier Transform
So I'm trying to understand how MRI machines work. I understand all the concepts of it, the parts, what they do, how the machine works, etc. The part I'm having trouble with is the fourier transform ...
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FFT, How to decide if there is a signal among noise?
I have sets of data of different deep sky objects. My job is to check for any periodicity.
I use IDL to run an FFT and wavelet methods to check for a signal. To test my code I ran the IDL built in ...
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Bridging CTFT and DTFT for a cosine
I'm trying to understand how I can start from the CTFT of a signal and end up with a DTFT.
For example if I take a basic example:
$$\begin{aligned}
x(t) &= \cos(\omega_x \cdot t) = \frac{1}{2} \...
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Understanding the meaning of amplitude in FFT
I am recording data with a magnetometer of the background magnetic field in a building. I have applied the FFT algorithm to the data in order to look for the frequencies that appear in it. I would ...
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How can understand periodicity of a Signal from frequency domain representation?
Is it possible to say a signal is periodic from its frequency domain representation? A periodic signal is sum of its sinus and cosinus. Frequency translation of sinus and cosinus functions are ...
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Response of a system to a step function (heaviside)
I'd like to compute the response to a step function of a electrical/thermal system. Generally I can "easily" compute the transfer function $H$:
$$H(\omega) = \frac{V_{out}(\omega)}{V_{in}(\omega)}$$
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Is it possible to do single vehicle tracking using Fourier transform?
I am working on a project in image processing which is based on importance of phase only reconstruction of a signal obtained using Fourier transform.For more information about phase only ...
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Fourier transform possible on non-rectangular part of an image
Dear Signal Processing readers,
I want to introduce 'noise' into parts of images.
Until now, I worked with rectangluar images for a similar purpose and did the following, using (inverse) Fourier ...
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Is $O (N \log N)$ FFT speed the fastest we can ever attain?
I am wondering about whether or not there is a theoretical limit as to the speed at which we can compute a DFT. We all know that the FFT executes in $O (N \log N)$ time. However, is this a lower bound ...
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Fourier Transform and Delta Function
I am very new to Fourier analysis, but I understand that through the use of the Fourier transform a signal in the time domain is displayed in the frequency domain, where frequency values are normally ...
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how to compute a discrete fourier transform on fragmented data
I have a list of collected data points that I need to take a DFT of, however with the problem that about one quarter of the data points in the middle are missing, and so even though the existing data ...
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What should the amplitude be when plotting 1-sided Amplitude Spectrum?
I have a continuous signal x(t) such that
$x(t)=12cos(6\pi t)+6cos(24\pi t)+3cos(30 \pi t)$
and is asked to sketch a 1-sided Amplitude Spectrum of the signal x(t) if sampled above the minimum ...
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Periodicity of the discrete-time Fourier Transform
The DTFT of a sequence $x[n]$ can be written as $$X(e^{j\omega}) = \sum_{n = -\infty}^{\infty} x[n] e^{-j\omega n}.$$
Is the smallest (fundamental) period in frequency of the DTFT always $2\pi$? Or ...
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From MFCC to Machine learning. What are the steps?
I was able to get a dataset with MFCC coefficients. However, depending on the length of my sound file I get a different sized matrix. As in, 13 (13 MFCC coefficients) by XXX, where XXX will vary ...
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Relationship Between Sampled Continuous and Discrete Time Signals
Consider the sketched system below. $x_c(t)$ is an arbitrary, continuous-time signal at the input and $s(t)$ is an impulse train, defined as $s(t)=\sum_{n=-\infty}^{\infty} \delta(t-nT)$, where T is ...
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Is it possible to decompose an image into basis images using MATLAB?
I have read that:
Using Fourier decomposition any arbitrary image can be represented as
summation of orthogonal basis images.
I want to see the basis images for any image say Lena or Cameraman, ...
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Malaysia Flight 370 Image Processing
I wish that all those people on that flight were with us, and maybe they still are, as I like to think they are on an island somewhere waiting to us to find them ... however, it does not look good...
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Fourier Transform Computer Vision Textbook
I am required extremely fast to fill the gap and learn Fourier Transform with application in Computer Vision.
It was easy to find mathematical aspects of Fourier Transform, but I am more interested ...
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How to get coefficients for sine/cosine function from complex FFT?
I'm working on a control system that measures the movement of a vibrating robot arm. Because there is some deadtime, I need to look into the future of the somewhat noisy signal. My idea was to use the ...
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Checking Parseval's Theorem for Gaussian Signal by Using Scipy
I'm trying to check Parseval's theorm for Gaussian signal. It's well known that fourier transform of $\exp(-t^2)$ is $\sqrt{\pi}\exp(-\pi^2 k^2)$. So I implement it by using quad and simps. I think ...
