ifft

问题 I'm studying the IFFT in Matlab by applying it to a Gaussian. According to Wikipedia tables, the Fourier transform pair would be F(w) = sqrt(pi/a) * exp(-w^2/(4a)) in frequency, and f(t) = exp(-at^2) in time. I modified the code in a previous question plus Cris Luengo's answer to perform this IFFT. a = 0.333; ts = 1e4; % time sampling L = 1000*ts; % no. sample points ds = 1/ts; f = -floor(L/2):floor((L-1)/2); % freq vector f = f/ts; w = 2*pi*f; % angular freq Y = sqrt(pi/a)*exp(-w.^2/(4*a));

问题 I've red through the matlabcentral discussion on fftshift and ifftshift but I don't understand completely what's the right thing to do for me. A bit more helpful for one aspect is this answer on stackoverflow. I have an array A with (equally-spaced) angular frequencies in the first column and the corresponding intensities in the second column. It has an arbitrary length (can be odd or even). It does not start with zero frequency, but essentially, I am interested in a time-shift tau of an

问题 I took the Fourier transform of an image in Matlab and now I want to take the inverse fourier but the result is a completely black picture instead of the original image. I think there is some step that I need to do before taking the inverse. Thank you for any help. The code: nasa=imread('nasaNoise _1_','jpg'); N_Fourier=fft2(nasa); N_Fourier=fftshift(N_Fourier); N_Fourier=abs(N_Fourier); N_Fourier=log(N_Fourier+1); N_Fourier=mat2gray(N_Fourier); %Now doing the inverse N_inverse=ifft2(N

问题 Closed . This question needs to be more focused. It is not currently accepting answers. Want to improve this question? Update the question so it focuses on one problem only by editing this post. Closed 3 years ago . In numpy , we have the following functions : import numpy from numpy.fft import fft2, ifft2, fftshift, ifftshift I would like to rewrite these functions in R. fft in R works just as fft or fft2 in python. Also for ifft2 , we have to do fft(,inverse=T) Now I would like to know how

问题 I have convoluted an image I created in matlab with a 2D Gaussian function which I have also defined in matlab and now I am trying to deconvolve the resultant matrix to see if I get the 2D Gaussian function back using the fft2 and ifft2 commands. However the matrix I get as a result is incorrect (to my knowledge). Here is the code for what I have done thus far: % Code for input image (img) [300x300 array] N = 100; t = linspace(0,2*pi,50); r = (N-10)/2; circle = poly2mask(r*cos(t)+N/2+0.5, r

问题 whether i just nest them ( iff(fft(audio)) ) or try window-by-window ( window the audio, do the fft , do the ifft , then invert the window, replacing zero with eps, then merge the samples back (trying abs here and there in the pipelines)) i get only noise. i know the ifft is only inverse to the fft with infinite precision arithmetic, infinitely many samples, etc (right?) i'm working with 64bit floating point and 44kHZ sample rate. but, i would expect to be able to at least hear the original

问题 Please, see the the description of both fftshift and ifftshift . I would like to understand how to call the above two functions in relationship with fft and fftn in Matlab. Let say that my signal has a certain frequency content; now, the frequency array can generally be stored as: f = (-N/2:N/2-1)*df; f = (1:N)*(df/2); f = [(0:N/2-1) (-N/2:-1)]; What is the best way to call fft , coupled with fftshift and ifftshift , for the 3 study cases early mentioned? What is the effect on the standard

问题 According to the convolution theorem, a convolution in the time domain is a product in the fft domain. With correct zero-padding, it works: % convolution in time domain a = [1 2 3]; b = [4 5 6]; c = conv(a,b); a_padded=[a 0 0]; b_padded=[b 0 0]; c_bis=ifft(fft(a_padded).*fft(b_padded)); % we do find c_bis=c However, this theorem is suposed to work the other way around as well, a product in the time domain is a convolution in the fft domain. I dont get this part: d = a.*b; D=conv(fft(a_padded)

问题 I'm having some trouble understanding how to use KissFFT (1.2.9) correctly. All I am trying to achieve for now is to perform an FFT and then immediately perform an iFFT to reconstruct the original signal again. The code snippet below demonstrates what I'm doing: void test(short* timeDomainData, int length) { // Create the configurations for FFT and iFFT... kiss_fftr_cfg fftConfiguration = kiss_fftr_alloc( length, 0, NULL, NULL ); kiss_fftr_cfg ifftConfiguration = kiss_fftr_alloc( length, 1,

问题 I try to filter a signal using opencv's dft function. The way I try to this is taking the signal in time domain: x = [0.0201920000000000 -0.0514940000000000 0.0222140000000000 0.0142460000000000 -0.00313500000000000 0.00270600000000000 0.0111770000000000 0.0233470000000000 -0.00162700000000000 -0.0306280000000000 0.0239410000000000 -0.0225840000000000 0.0281410000000000 0.0265510000000000 -0.0272180000000000 0.0223850000000000 -0.0366850000000000 0.000515000000000000 0.0213440000000000 -0