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Signal Processing Course: Fourier Processing
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Gabriel Peyré
January 01, 2012
Research
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Signal Processing Course: Fourier Processing
Gabriel Peyré
January 01, 2012
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Transcript
Fourier Processing Gabriel Peyré http://www.ceremade.dauphine.fr/~peyre/numerical-tour/
Overview •Continuous Fourier Basis •Discrete Fourier Basis •Sampling •2D Fourier
Basis •Fourier Approximation
m (x) = em (x) = e2i mx Continuous Fourier
Bases Continuous Fourier basis:
m (x) = em (x) = e2i mx Continuous Fourier
Bases Continuous Fourier basis:
Fourier and Convolution
Fourier and Convolution x− x+ x 1 2 1 2
f f ∗1[− 1 2 , 1 2 ]
Fourier and Convolution x− x+ x 1 2 1 2
f f ∗1[− 1 2 , 1 2 ] 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1
Fourier and Convolution x− x+ x 1 2 1 2
f f ∗1[− 1 2 , 1 2 ] 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1
Overview •Continuous Fourier Basis •Discrete Fourier Basis •Sampling •2D Fourier
Basis •Fourier Approximation
Discrete Fourier Transform
Discrete Fourier Transform
Discrete Fourier Transform ˆ g[m] = ˆ f[m] · ˆ
h[m]
Discrete Fourier Transform ˆ g[m] = ˆ f[m] · ˆ
h[m]
Overview •Continuous Fourier Basis •Discrete Fourier Basis •Sampling •2D Fourier
Basis •Fourier Approximation
Infinite continuous domains: Periodic continuous domains: Infinite discrete domains: Periodic
discrete domains: f0 (t), t R f0 (t), t ⇥ [0, 1] R/Z The Four Settings ˆ f[m] = N 1 n=0 f[n]e 2i N mn ˆ f0 ( ) = +⇥ ⇥ f0 (t)e i tdt ˆ f0 [m] = 1 0 f0 (t)e 2i mtdt ˆ f( ) = n Z f[n]ei n Note: for Fourier, bounded periodic. .. . .. . .. . .. . f[n], n Z f[n], n ⇤ {0, . . . , N 1} ⇥ Z/NZ
ˆ f[m] = N 1 n=0 f[n]e 2i N mn
Fourier Transforms Discrete Infinite Periodic f[n], n Z f[n], 0 n < N Periodization Continuous f0 (t), t R f0 (t), t [0, 1] f0 (t) ⇥ n f0 (t + n) Sampling ˆ f0 ( ) ⇥ { ˆ f0 (k)}k Discrete Infinite Periodic Continuous Sampling ˆ f[k], 0 k < N ˆ f0 ( ), R ˆ f0 [k], k Z Fourier transform Isometry f ⇥ ˆ f ˆ f0 ( ) = +⇥ ⇥ f0 (t)e i tdt ˆ f0 [m] = 1 0 f0 (t)e 2i mtdt ˆ f( ) = n Z f[n]ei n ˆ f(⇥), ⇥ [0, 2 ] Periodization ˆ f(⇥) = k ˆ f0 (N(⇥ + 2k )) f[n] = f0 (n/N)
Sampling and Periodization (a) (c) (d) (b) 1 0
Sampling and Periodization: Aliasing (b) (c) (d) (a) 0 1
Uniform Sampling and Smoothness
Uniform Sampling and Smoothness
Uniform Sampling and Smoothness
Uniform Sampling and Smoothness
Overview •Continuous Fourier Basis •Discrete Fourier Basis •Sampling •2D Fourier
Basis •Fourier Approximation
2D Fourier Basis em [n] = 1 N e 2i
N0 m1n1+ 2i N0 m2n2 = em1 [n1 ]em2 [n2 ]
2D Fourier Basis em [n] = 1 N e 2i
N0 m1n1+ 2i N0 m2n2 = em1 [n1 ]em2 [n2 ]
Overview •Continuous Fourier Basis •Discrete Fourier Basis •Sampling •2D Fourier
Basis •Fourier Approximation
1D Fourier Approximation
1D Fourier Approximation 0 0.2 0.4 0.6 0.8 1 0
0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1
2D Fourier Approximation