ifft

问题 I am currently trying to compare a simple inverse filter to the wiener filter for deconvolution using matlab. My starting signal is exp(-t^2) and this is to be convolved with a rect that is nonzero for times -.5 to .5. I am introducing noise with amplitude in the range -.5 to .5. Defining my time domain to frequency domain mapping: f = exp(-t^2) => F s = rect => R c = f*s => C r = noise (see above) => R with noise c becomes: c = f*s + n => C = FxS + N For the first approach I am simply taking

问题 I'm trying to increase / decrease the frequency of a signal using fft and ifft. The first plot is 1hz and the second plot is 2hz which I'm trying to get by altering the fft and ifft values . I can go between the frequency domain and time domain but how can I increase or decrease the frequency of the signal using fft / ifft? Note: Yes I know I could change the frequency by changing the frequency value of the equation but I'm just using that as a test signal. The signals I will be using won't

问题 I have the following code that has bug when doing the inverse FFT. The forward FFT works as I printed the output and verified it. But the inverse does not seem to. Any ideas? Does it look like I have missed a concept? Code - http://pastebin.com/iZYtdcqR EDIT - I have essentially rewritten the code that comes with the CUDA toolkit samples. I am trying to perform a convolution using FFT but with a modified algorithm (DIF actually.) EDIT2 - dding code to the question. #include <stdio.h> #include

问题 I have a current signal (extracted in csv) which I obtained from cadence simulation over 30ns time. I have removed DC offset and applied windowing function before FFT. And normalized FFT by sqrt(N) . I have shift zero-frequency component to center of my desired spectrum with fftshift(X) . I got my desired FFT. I also want to get back to my original windowed signal by ifft but it is not showing my windowed signal instead it is showing only a version of the window function that I used. My

问题 I have a current signal (extracted in csv) which I obtained from cadence simulation over 30ns time. I have removed DC offset and applied windowing function before FFT. And normalized FFT by sqrt(N) . I have shift zero-frequency component to center of my desired spectrum with fftshift(X) . I got my desired FFT. I also want to get back to my original windowed signal by ifft but it is not showing my windowed signal instead it is showing only a version of the window function that I used. My

问题 I want to remove the Gibbs artifact in a 1D signal by applying the Hamming filter on that in MATLAB. What I have is the k1 which is the signal in frequency domain. I can get the signal in time domain by applying DFT on k1 : s1 = ifft(ifftshift(k1)); This signal has Gibbs artifact. Now, I want to remove it by (A) multiplying Hamming filter to k1 in teh frequency domain and (B) convolving IFFT of Hamming filter with s1 in the spatial domain. I am expecting same output from both of these: % (A)

问题 I want to remove the Gibbs artifact in a 1D signal by applying the Hamming filter on that in MATLAB. What I have is the k1 which is the signal in frequency domain. I can get the signal in time domain by applying DFT on k1 : s1 = ifft(ifftshift(k1)); This signal has Gibbs artifact. Now, I want to remove it by (A) multiplying Hamming filter to k1 in teh frequency domain and (B) convolving IFFT of Hamming filter with s1 in the spatial domain. I am expecting same output from both of these: % (A)

问题 Hi guy's I'm working on simple signals and I want to calculate the Fourier transform of a signal, get the magnitude and phases, then reconstruct the original signal from that. I'm basing my code on this thread. Code: >> n=0:99; >> N=length(n); >> x = sin((2*pi/N).*n).*cos((pi/N).*n); >> F = fft(x); >> mag = sqrt(real(F).^2 + imag(F).^2); >> phase = atan2(imag(F),real(F)); >> re = mag .* cos(phase); >> im = mag .* sin(phase); >> F_i = re + 1i*im; >> x_i = ifft(F_i); >> figure;stem(x);figure

问题 I want to use Fast Fourier Transform but already trying a simple back and forth transformation doesn't work. The code is import cv2 import numpy as np img = cv2.imread('Picture.bmp',0) f = np.fft.fft2(img) fshift = np.fft.fftshift(f) f_ishift = np.fft.ifftshift(fshift) img_back = cv2.idft(f_ishift) img_back = cv2.magnitude(img_back[:,:,0],img_back[:,:,1]) and the error is Traceback (most recent call last): File "test.py", line 8, in <module> img_back = cv2.idft(f_ishift) TypeError: src data

问题 This question already has an answer here : FFT Images and its Inverse (1 answer) Closed 4 years ago . I have a problem with converting amplitude and phase data into the complex form, which is required to perform an IFFT. (inverse fast fourier transform). This is the only data I have. My frequency range goes from 0.1 to 2.6 and, with 200 samples. I would like to use IFFT to obtain a time signal. How do I convert this magnitude and phase dataset into the complex plane? I have never used IFFT