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CE 40763 CE 40763

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CE 40763 - PPT Presentation

Digital Signal Processing Fall 1992 Fast Fourier transform FFT Hossein Sameti Department of Computer Engineering Sharif University of Technology Many reallife systems can be modeled by LTI systems ID: 257309

hossein sharif university technology sharif hossein technology university computer dept eng sameti decimation dft time frequency output input adds

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Slide1

CE 40763Digital Signal ProcessingFall 1992Fast Fourier transform (FFT)

Hossein SametiDepartment of Computer Engineering Sharif University of TechnologySlide2

Many real-life systems can be modeled by LTI systems  use convolution for computing the output  use DFT to compute convolutionFast Fourier Transform (FFT) is a method for calculating Discrete Fourier Transform (DFT) Only faster!Definition of DFT:How many computations?Motivation

2

N

pt. DFT of

x(n)

Q: For each

k

:

How many adds and how many mults?

A

: (N-1)

complex adds and

N complex mults.

How many k values do we have?

N

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide3

Motivation3

Direct computation:

FFT:

Ideal case:

N

Direct

FFT

10^3

O(10^6)

O(10^3*log10^3)=O(10^4)

10^6

O(10^12)

O(10^6*log10^6)=O(2*10^7)

Example:

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide4

4Algorithms for calculating FFT

FFTDecimation in timeDecimation in frequency

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide5

Decimation in time5

The main idea: use the

divide and conquer

method

It works by recursively breaking down a problem into two or more sub-problems of the same (or related) type, until these become simple enough to be solved directly.

The solutions to the sub-problems are then combined to give a solution to the original problem.

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide6

Decimation in time6

N

: power of 2

n

: even

n

: odd

n

: even

n=2r

r:0

N/2-1

n:0

N-2

n

: odd

n

=2

r

+1

r:0

N/2-1

n:1

N-1

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide7

7Decimation in time

Suppose:

What are

G(k)

and

H(k)

?Slide8

8Decimation in time

In

G(k)

and

H(k)

,

k

varies between 0 and

N/2-1

.

However, in

X(k) , k varies between 0 and N-1.

Solution: use the relationship between DFS and DFT.

We thus need to replicate G(k) and H(k) “once”, to get X(k).

Hossein Sameti, Dept. of Computer Eng., Sharif University of Technology Slide9

9Decimation in time

g(r)

h(r)

pt. DFT

pt. DFT

+

(twiddle factor)

After replication

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide10

10Decimation in time

g(r)

h(r)

pt. DFT

pt. DFT

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide11

11Example of Decimation in time (

N=8)

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide12

12Example of Decimation in time (

N=8)

N/2

pt. DFT block

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide13

13Example of Decimation in time (

N=8)

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide14

14Example of Decimation in time (

N=8)

r(0)

r(1)

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide15

15Example of Decimation in time (

N=8)

r(0)

r(1)

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide16

16Example of Decimation in time (

N=8)

Flow graph of a the 2-pt. DFT

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide17

17Example of Decimation in time (

N=8)

How many stages do we have?

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide18

General form of a butterfly18

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide19

19Revised form of a butterfly

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide20

20Revised form of a butterfly

2 mults+ 2 adds

1 mult+ 2 adds

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide21

Final figure for 8-pt DFT21

In-place computation (only

N

storage locations are needed)

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide22

Computational complexity22

How many stages do we have

Each stage has

N

inputs and

N

outputs.

Each butterfly has

2

inputs and

2

outputs.

Each stage has butterflies.

Each butterfly needs 1 mult and 2 adds.

Total number of operations:

adds

mults

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide23

Indexing of the inputs and outputs23

Output indexing is in order.

input indexing is shuffled.

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide24

Bit reversing24

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide25

Re-arranging the input order25

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide26

Re-arranging the input order26

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide27

Decimation in frequency27

The main idea: use the

divide and conquer

method (this time in the frequency domain)

Divide the computation into two parts: even indices of

k

and odd indices of

k

.

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide28

28Decimation in frequency

1

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide29

29Decimation in frequency

N/2 pt. DFT of

g(n)

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide30

30

Decimation in frequency

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide31

31Decimation in frequency

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide32

32Decimation in frequency

-1

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide33

33Decimation in frequency

N/2 pt. DFT of

h(n)

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide34

34

Decimation in frequency

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide35

35Decimation in frequencySlide36

Format of the Last stage Butterfly in Decimation in frequency 36

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide37

37Decimation in frequency

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide38

38Decimation in frequency (re-order the output)

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide39

39Decimation in frequency (ordered input and output)

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide40

Change x with X (i.e., input nodes with output nodes)Change X with x (i.e., output nodes with input nodes)Reverse the order of the flow graphs.The same system function is achieved.

40

Transposition theorem

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide41

41Decimation in frequency

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide42

Transposed version of the previous figure (Decimation in Time)42

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology Slide43

How can we deal with twiddle factors?Should we store them in a table (i.e, use a lookup table) or should we calculate them?What happens if N is not a factor of 2?It can be shown that if N=RQ, then an N pt. DFT can be expressed in terms of R Q-pt. DFT or Q R pt. DFTs (Cooley-Tukey algorithm).

Practical issues

43

Hossein

Sameti, Dept. of Computer Eng., Sharif University of Technology

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