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Seismic Data Processing Lecture 4 Fourier Series and Fourier Transform Prepared by Dr. Amin E. Khalil School of Physics, USM, Malaysia

Seismic data processing lecture 4

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Page 1: Seismic data processing lecture 4

Seismic Data ProcessingLecture 4

Fourier Series and Fourier TransformPrepared by

Dr. Amin E. KhalilSchool of Physics, USM, Malaysia

Page 2: Seismic data processing lecture 4

Today's Agenda

• Examples on Fourier Series

• Definition of Fourier transform

•Examples on Fourier transform

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Examples on Fourier Series

Example: 1

Solution:

The function f(x) is an odd function, thus the a- terms vanishes and the transform will be:

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Increasing the number of terms we arrive at better approximation.

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Another Example

The function is even function and thus:

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Fourier-Discrete Functions

iN

xi2

.. the so-defined Fourier polynomial is the unique interpolating function to the function f(xj) with N=2m

it turns out that in this particular case the coefficients are given by

,...3,2,1,)sin()(2

,...2,1,0,)cos()(2

1

*

1

*

kkxxfN

b

kkxxfN

a

N

jjj

N

jjj

k

k

)cos(2

1)sin()cos(

2

1)( *

1

1

****0 kxakxbkxaaxg m

m

km kk

... what happens if we know our function f(x) only at the points

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Fourier Spectrum

)(

)(arctan)(arg)(

)()()()(

)()()()(

22

)(

R

IF

IRFA

eAiIRF i

)(

)(

A Amplitude spectrum

Phase spectrum

In most application it is the amplitude (or the power) spectrum that is of interest.

Remember here that we used the properties of complex numbers.

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When does the Fourier transform work?

Gdttf )(

Conditions that the integral transforms work:

f(t) has a finite number of jumps and the limits exist from both sides

f(t) is integrable, i.e.

Properties of the Fourier transform for special functions:

Function f(t) Fouriertransform F(w)

even even

odd odd

real hermitian

imaginary antihermitian

hermitian real

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Some properties of the Fourier Transform

Defining as the FT: )()( Ftf

Linearity

Symmetry

Time shifting

Time differentiation

)()()()( 2121 bFaFtbftaf

)(2)( Ftf

)()( Fettf ti

)()()( Fi

t

tf nn

n

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Time differentiation )()()( Fi

t

tf nn

n

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Examples on Fourier Transform

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Graphically the spectrum is:

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Important applications of FT

• Convolution and Deconvolution

• Filtering

• Sampling of Seismic time series

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Thank you