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The dft, fft, and practical
Fast fourier transform algorithms
Multidimensional index maps
Multidimensional index maps for dif and dit
algorithms
Decimation-in-time algorithm
Radix-2 DIT :
X
k
n
N
1
0
x
n
W
N
n
k
n
N
2
1
0
x
2
n
W
N
2
n
k
n
N
2
1
0
x
2
n
1
W
N
(
2
n
+
1
)
k Formalization: Let
n
n
1
2
n
2 :
n
1
:
n
2
X
k
n
N
1
0
x
n
W
N
n
k
n
1
1
0
n
2
N
2
1
0
x
n
1
2
n
2
W
N
(
n
1
+
2
n
2
)
k Also, let
k
N
2
k
1
k
2 :
k
1
:
k
2
As long as there is a one-to-one correspondence
between the original indices
and the
n ,
k generated by the index
map, the computation is the
same ;
only the order in which the sums are done is changed.
Rewriting the
DFT formula in terms of index map
n
n
1
2
n
2 ,
k
N
2
k
1
k
2 :
X
k
X
N
2
k
1
k
2
n
N
1
0
x
n
W
N
n
(
N
2
k
2
+
k
2
)
n
1
1
0
n
2
N
2
1
0
x
n
1
2
n
2
W
N
(
n
1
+
n
2
)
(
N
2
k
1
+
k
2
n
1
1
0
n
2
N
2
1
0
x
W
N
N
2
n
1
k
2
W
N
n
1
k
2
W
N
N
n
2
k
1
W
N
2
n
2
k
2
n
1
1
0
n
2
N
2
1
0
x
W
2
n
1
k
2
W
N
n
1
k
2
1
W
N
2
n
2
k
2
n
1
1
0
W
2
n
1
k
2
W
N
n
1
k
2
n
2
N
2
1
0
x
W
N
2
n
2
k
2
Key to FFT is choosing index map so that one of the
cross-terms disappears!
For arbitrary composite
N
N
1
N
2 , we can define an index map
n
n
1
N
1
n
2
k
N
2
k
1
k
2
n
1
k
1
n
2
k
2
X
k
X
k
1
k
2
n
1
N
1
1
0
n
2
N
2
1
0
x
n
1
n
2
W
N
N
2
n
1
k
1
W
N
n
1
k
2
W
N
N
k
1
n
2
W
N
N
1
n
2
k
2
n
1
N
1
1
0
n
2
N
2
1
0
x
n
1
n
2
W
N
1
n
1
k
1
W
N
n
1
k
2
1
W
N
2
n
2
k
2
DFT
n
1
,
N
1
W
N
n
1
k
2
DFT
n
2
,
N
2
x
n
1
n
2
Computational cost in multipliesl "common factor
algorithm (cfa)"
N
1 length-
N
2 DFTs
N
1
N
2
2
N twiddle factors
N
N
2 length-
N
1 DFTs
N
2
N
1
2
Total
N
1
N
2
2
N
1
N
2
N
2
N
1
2
N
N
1
N
2
1
"Direct":
N
2
N
N
1
N
2
Pictorial representations
Emphasizes multi-dimensional structure
Emphasizes computer memory organization
Easy to draw
n
n
1
5
n
2 ,
k
3
k
1
k
2
Source:
OpenStax, The dft, fft, and practical spectral analysis. OpenStax CNX. Feb 22, 2007 Download for free at http://cnx.org/content/col10281/1.2
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