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exercise/1. Introduction Julia/Julia Installation.html
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exercise/1. Introduction Julia/Julia Installation.html
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exercise/1. Introduction Julia/Julia Intro - exercise.jl
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exercise/1. Introduction Julia/Julia Intro - exercise.jl
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exercise/2. Signal Processing/exercise2.zip
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exercise/2. Signal Processing/exercise2.zip
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lecture/3. Signal Processing/code_signal_processing.jl
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lecture/3. Signal Processing/code_signal_processing.jl
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using Images
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using PyPlot
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using FFTW
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N = 64
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x = shepp_logan(N)
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figure(1)
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clf()
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subplot(2,2,1)
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imshow(x)
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X = fft(x)
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subplot(2,2,2)
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imshow(abs.(X))
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Y = fftshift(X)
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subplot(2,2,3)
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imshow(abs.(Y))
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Y[1:div(N,4)+1,:] .= 0.0
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Y[3*div(N,4):end,:] .= 0.0
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Y[:,1:div(N,4)+1] .= 0.0
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Y[:,3*div(N,4):end] .= 0.0
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subplot(2,2,4)
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imshow(abs.(Y))
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figure(2)
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clf()
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imshow(abs.(ifft(ifftshift(Y))))
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function mydft(x)
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N = length(x)
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y = zeros(ComplexF64,N)
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for l=1:N
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for n=1:N
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y[l] += x[n]*exp(-2*pi*im*(n-1)*(l-1)/N)
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end
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end
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return y
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end
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lecture/4. Radiography/4. Radiography.pdf
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lecture/4. Radiography/4. Radiography.pdf
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tutorials/1. Introduction to Julia Programming.zip
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tutorials/1. Introduction to Julia Programming.zip
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tutorials/webcam.jl
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tutorials/webcam.jl
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