6 i 7 Fourier Transform Properties

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Fourier Transform
Properties

„Signal Theory” Zdzisław Papir

Linearity

Conjugate operation

Amplitude and phase spectra

Scaling

Symmetry

Shifting in time

Shifting in frequency

Modulation

Convolution in time

Signal ‘area’

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Differentiation in time domain

Integration in time domain

Real and imaginary parts of a signal

Limiting properties of Fourier transform

Parseval and Rayleigh theorems

Energy spectrum; fractional energy

„Signal Theory” Zdzisław Papir

Fourier Transform
Properties

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Fourier transform properties

Basic assumptions

 

 

 

 

Y

t

y

X

t

x

„Signal Theory” Zdzisław Papir

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LINEARITY

 

 

 

 

 

 

 

 

Y

X

t

y

t

x

t

y

t

x

t

y

t

x

F

F

F

F

F

Fourier transform properties

„Signal Theory” Zdzisław Papir

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CONJUGATE OPERATION

 

 

*

*

X

t

x

For a real signal the formula holds:

 

 

 

 

 

*

*

,

X

X

t

x

t

x

t

x

R

Fourier transform properties

„Signal Theory” Zdzisław Papir

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AMPLITUDE and PHASE SPECTRA

 

 

 

 

 

 

spectrum

phase

-

spectrum

amplitude

-

e

A

A

X

t

x

j

For a real signal the formula holds:

 

 

 

 

function

odd

an

is

spectrum

phase

-

function

even

an

is

spectrum

amplitude

-

A

A

Fourier transform properties

„Signal Theory” Zdzisław Papir

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 

2

2

2

1

1

1

1

1

1

1

j

j

j

e

t

t

1

 

 

 

arctg

1

1

2

A

Fourier transform properties

AMPLITUDE and PHASE SPECTRA

„Signal Theory” Zdzisław Papir

frequency

amplitude spectrum

phase spectrum

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SCALING

 

0

,

1

1

e

1

j

j

t

t

1

 

X

t

x

1

Squeezing signal in the time domain broadens its
spectrum; extending a signal narrows its spectrum.

The shorter is the signal the broader is its spectrum.

„Signal Theory” Zdzisław Papir

Fourier transform properties

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SYMMETRY

Fourier transform properties

„Signal Theory” Zdzisław Papir

 

 

 

 

x

t

X

X

t

x

2

 

 

 

 

W

T

T

W

Wt

tT

T

T

T

t

2

Sa

2

2

/

Sa

2

Sa

W

T

2

 

 

W

W

Wt

2

Sa

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SYMMETRY

 

 

 

 

x

t

X

X

t

x

2

 

 

 

 

 

 

 

 

 

x

t

X

d

e

x

d

e

x

t

X

d

e

x

t

X

t

dt

e

t

x

X

t

j

t

j

t

j

t

j

2

2

2

1

Fourier transform properties

„Signal Theory” Zdzisław Papir

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SHIFTING in TIME

Change of a phase spectrum:

 

 

 

 

 







j

j

j

j

A

A

X

e

e

e

e

 



j

e

X

t

x

Fourier transform properties

„Signal Theory” Zdzisław Papir

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SHIFTING in FREQUENCY

 

o

o

e

X

t

x

t

j

Fourier transform properties

„Signal Theory” Zdzisław Papir

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MODULATION

  

  

 

o

o

o

o

o

o

o

2

1

cos

exp

exp

X

X

t

t

x

X

t

j

t

x

X

t

j

t

x

X(

)

X(

-

o

)/2

X(

+

o

)/2

-

o

+

o

Fourier transform properties

„Signal Theory” Zdzisław Papir

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CONVOLUTION in TIME

   

  



d

t

y

x

t

y

t

x

PROPERTIES

Commutation

   

   

t

x

t

y

t

y

t

x

Association

   

 

 

   

t

z

t

y

t

x

t

z

t

y

t

x

Distribution with
addition

 

   

       

t

z

t

x

t

y

t

x

t

z

t

y

t

x

Fourier transform properties

„Signal Theory” Zdzisław Papir

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Commutation

   

  

d

t

y

x

t

y

t

x

   

   

t

x

t

y

t

y

t

x

)

(

)

(

t

y

t

x

d

t

y

x

)

(

)

(

dz

d

z

t

   

t

x

t

y

dz

z

y

z

t

x

)

(

)

(

„Signal Theory” Zdzisław Papir

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CONVOLUTION in TIME

   

  



d

t

y

x

t

y

t

x

„Signal Theory” Zdzisław Papir

Fourier transform properties

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„Signal Theory” Zdzisław Papir

CONVOLUTION in TIME

expresses the amount of overlap

of one function x(τ) as it is shifted over another function y(τ).

0

1

 

x

1

0

2

 

y

1

0

-2

 

y

1

t

y

1

t

1

t

y

1

2

t

  

2

2

t

t

S

d

t

y

x

S



t - 2

t

0

S

Fourier transform properties

t

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Convolution in time

„Signal Theory” Zdzisław Papir

 

dt

d

y

t

x

t

j

e

)

(

)

(

)

(

)

(

t

y

t

x

 

d

y

dt

e

t

x

t

j

)

(

)

(

dz

dt

z

t

 

d

y

dz

e

z

x

z

j

)

(

)

(

)

(

background image

 

d

y

dz

e

z

x

z

j

)

(

)

(

)

(

 



d

y

dz

e

z

x

j

z

j

e

)

(

)

(



d

y

X

j

e

)

(

)

(

)

(

)

(

Y

X

)

(

)

(

t

y

t

x

Convolution in time

„Signal Theory” Zdzisław Papir

background image

„Signal Theory” Zdzisław Papir

CONVOLUTION in FREQUENCY

   

   

   

  

d

Y

X

t

y

t

x

Y

X

t

y

t

x

2

1

2

1

Fourier transform properties

background image

„Signal Theory” Zdzisław Papir

SIGNAL ‘AREA’ (dc component of the signal)

 

 

 

0

0

0

X

X

dt

e

t

x

dt

t

x

t

j





Fourier transform properties

 

 

W

W

dt

Wt

Wt

W

Wt

Wt

Wt

W

W

0

sin

sin

Sa

2

2

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„Signal Theory” Zdzisław Papir

 

W

W

W

W

W

W

W

dt

Wt

Wt

sgn

0

,

0

,

sin



 

 

 

sgn

0

,

0

,

1

sin

sin

1

j

j

j

j

t

dt

t

t

j

dt

t

t

j

dt

t

e

t

t

j

F

F

 

 

j

t

j

t

2

sgn

sgn

1

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„Signal Theory” Zdzisław Papir

DIFFERENTIATION in TIME

 

 

 

 

 

0

lim

,



t

x

X

j

dt

t

dx

X

t

x

t

 

 

 

 

 

 

 

 





X

j

dt

e

t

x

j

e

x

e

x

dt

e

t

x

j

e

t

x

dt

e

t

x

dt

t

dx

t

j

j

j

t

j

t

j

t

j



lim

lim

F

DIFFERENTIATION in TIME

emphasizes rapid changes

of signal level what is reflected in a relative „amplification”
of higher frequencies (responsible for these changes).

Fourier transform properties

background image

„Signal Theory” Zdzisław Papir

INTEGRATION in TIME

 

 

 

   

 

j

X

X

d

x

X

t

x

t

0

If the signal does not contain a dc component,
X
(

= 0) = 0, then:

 

 

 

 

j

X

d

x

X

t

x

t

Fourier transform properties

INTEGRATION in TIME

smooths rapid changes

of a signal level by a relative attenuation of high frequencies.

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„Signal Theory” Zdzisław Papir

INTEGRATION in TIME

 

   

  

 

 

 

 

t

X

d

x

t

t

t

d

t

x

t

t

x

d

x

t

t

1

1

1

1

F

,

0

,

1

The proof of the property

INTEGRATION in TIME

is based on a convolution representation
of an integral.

 

0

,

1

0

,

0

t

t

t

1

Fourier transform properties

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„Signal Theory” Zdzisław Papir

REAL and IMAGINARY PARTS of the SIGNAL

 

 

 

 

 

 

 

 

j

X

X

t

x

X

X

t

x

2

2

*

*

Im

Re

Fourier transform properties

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„Signal Theory” Zdzisław Papir

EVEN and ODD SIGNALS

Fourier transform properties

     

 

 

R

R

dt

t

t

x

X

t

x

t

x

t

x

0

cos

2

,

even signal real Fourier transform

 

   

 

 

dt

t

t

x

j

X

t

x

t

x

t

x

0

sin

2

,

R

odd signal imaginary Fourier transform

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„Signal Theory” Zdzisław

Papir

EVEN and ODD PARTS of the SIGNAL

Fourier transform properties

 

 

 

 

   

 

   

2

2

o

e

p

n

t

x

t

x

t

x

t

x

t

x

t

x

t

x

t

x

t

x

 

 

 

 

X

j

t

x

X

t

x

Im

Re

o

e

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„Signal Theory” Zdzisław Papir

LIMITING PROPERTIES
of FOURIER TRANSFORM (Riemann)

 

0

lim

X

Decaying rate of Fourier transform (for T-pulses) is:

provided continuous derivatives exist

 

 

const

X

X

n

n

n

2

2

2

lim

1

lim

0

1

lim

Fourier transform properties

.

frequency

with

0

ansform

Fourier tr

 

2

2

T

x

T

x

n

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 

,

1

4

4

sin

2

1

4

Sa

2

1

2

2

2

2

T

T

T

T

T

t

T

T/2

-T/2

 

t

T

T/2

-T/2

 

 

t

T

1

 

 

t

T

2

4

Sa

2

1

2

T

T

2

1

„Signal Theory” Zdzisław Papir

LIMITING PROPERTIES
of FOURIER TRANSFORM

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„Signal Theory” Zdzisław Papir

LIMITING PROPERTIES
of FOURIER TRANSFORM

-5

-4

-3

-2

-1

0

1

2

3

4

5

0

+T/2

-T/2

Pulse „raised cosine

 

 

3

2

2

2

1

~

2

2

sin

2

,

2

,

2

cos

1

2

1

T

T

X

T

T

t

t

T

t

x

T

T



background image

PARSEVAL THEOREM

 

 

 

 

0

2

2

2

1

2

1

d

X

d

X

dt

t

x

E

t

x

R

i(t) = x(t)

u(t) = x(t)

E

   

 





dt

t

x

dt

t

i

t

u

E

2

R = 1

„Signal Theory” Zdzisław Papir

Fourier transform properties

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PARSEVAL THEOREM

dt

t

x

2

)

(

dt

t

x

t

x

)

(

)

(

*

dt

d

e

X

t

x

t

j

)

(

2

1

)

(

*

d

dt

e

t

x

X

t

j

)

(

)

(

2

1

*

d

X

X

)

(

)

(

2

1

*

d

X

2

)

(

2

1

„Signal Theory” Zdzisław Papir

background image

Marc-Antoine PARSEVAL (1755 - †1836)

Very little is known of Antoine Parseval's life.

Parseval had only
five publications, all presented to the Académie des
Sciences.
The second was Mémoire sur les séries et sur
l'intégration complète
d'une équation aux differences partielle linéaires du
second ordre,
à coefficiens constans
dated 5 April 1799, contains the
result known
today as Parseval's theorem.

Parseval's result was not published until his five

papers were all
published by the Académie des Sciences in 1806.
Before that it was
known by members of the Academy and appeared in
works by Lacroix
and Poisson before Parseval's papers were printed.

Parseval was never honoured with election to

the Académie
des Sciences. He remains a somewhat shadowy figure
and it is hoped
that research will one day provide a better
understanding of his life
and achievements.

 

 





d

X

dt

t

x

2

2

2

1

(no picture available)

„Signal Theory” Zdzisław Papir

background image

RAYLEIGH THEOREM

   

   

   

d

Y

X

dt

t

y

t

x

t

y

t

x

*

*

2

1

,

C

Rayleigh theorem is the Parseval theorem
stated for two different signals.

„Signal Theory” Zdzisław Papir

Fourier transform properties

background image

FRACTIONAL ENERGY

ENERGY SPECTRAL DENSITY

 

 

 

 

 

2

2

2

1

1

,

X

S

X

dv

v

X

E

E

 

 

 

 

 

E

E

E

dv

v

X

E

dv

v

X

E

E

u

o

2

o

2

1

0

,

1

,

0

„Signal Theory” Zdzisław Papir

Fourier transform properties

background image

 

2

Sa

T

T

t

T

FRACTIONAL ENERGY

„Signal Theory” Zdzisław Papir

Fourier transform properties

frequency f

rectangular pulse – fractional energy

amplitude spectrum

fractional energy

 

 

0

,

Sa

2

o

2

u

f

dv

v

f

E

fT

background image

Summary

In most cases we determine Fourier transforms using
previously proved properties and known Fourier
transform pairs.
It is not recommended to use the definition formulas
of the Fourier transform.

Convolution and Parseval theorems are of most
considerable significance.

Convolution concept is used for signal filtering description.

Parseval theorem is a starting point for a spectral analysis
of random processes.


Document Outline


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