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Transforms
M.Starwin
Need for Transform
• Transforms make some types of calculations
much simpler and more convenient.
• Transforms are tools to make analysis easier.
• Laplace transform, for example, makes solving
differential equations easier.
• Possible to do all computation and analysis of
a signal in either the time domain or the
frequency domain.
Fourier Transform
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Discrete Time Fourier Transform Pair
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Synthesis Inverse Fourier Transform
(IFT)
Fourier Transform
(FT)
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Discrete Fourier Transform
DFT
IDFT
DFT PROPERTIES
Periodicity
If 𝑥 𝑛 ↔ 𝑋 𝑘
𝑥(𝑛 + 𝑁) = 𝑥 𝑛 𝑓𝑜𝑟 𝑎𝑙𝑙 𝑛
𝑋 𝑘 + 𝑁 = 𝑋 𝑘 𝑓𝑜𝑟 𝑎𝑙𝑙 𝑘
DFT is defined as 𝑋 𝑘 =
𝑛=0
𝑁−1
𝑥(𝑛)𝑒−
𝑗2𝜋𝑛𝑘
𝑁
, 0≤𝑘≤𝑁−1
Sub k=k+N 𝑋 𝑘 + 𝑁 = 𝑛=0
𝑁−1
𝑥(𝑛)𝑒−
𝑗2𝜋𝑛(𝑘+𝑁)
𝑁
Cond..
𝑋 𝑘 + 𝑁 =
𝑛=0
𝑁−1
𝑥(𝑛)𝑒−
𝑗2𝜋𝑛𝑘
𝑁 𝑒−
𝑗2𝜋𝑛𝑁
𝑁
𝑋 𝑘 + 𝑁 =
𝑛=0
𝑁−1
𝑥(𝑛)𝑒−
𝑗2𝜋𝑛𝑘
𝑁
[𝑒−𝑗2𝜋𝑛
= 1]
𝑋 𝑘 + 𝑁 = 𝑋 𝑘
Hence Proved.
Linearity
• If 𝑥1 𝑛 ↔ 𝑋1 𝑘 𝑎𝑛𝑑 𝑥2 𝑛 ↔ 𝑋2 𝑘
Then ∝ 𝑥1 𝑛 + β𝑥2 𝑛 ↔ α𝑋1 𝑘 + β𝑋2 𝑘
DFT is defined as 𝑋 𝑘 = 𝑛=0
𝑁−1
𝑥(𝑛)𝑒−
𝑗2𝜋𝑛𝑘
𝑁
=
𝑛=0
𝑁−1
[∝ 𝑥1 𝑛 + β𝑥2 𝑛 ]𝑒−
𝑗2𝜋𝑛𝑘
𝑁
=
𝑛=0
𝑁−1
∝ 𝑥1 𝑛 𝑒−
𝑗2𝜋𝑛𝑘
𝑁 +
𝑛=0
𝑁−1
β𝑥2 𝑛 𝑒−
𝑗2𝜋𝑛𝑘
𝑁
=∝
𝑛=0
𝑁−1
𝑥1 𝑛 𝑒−
𝑗2𝜋𝑛𝑘
𝑁 + β
𝑛=0
𝑁−1
𝑥2 𝑛 𝑒−
𝑗2𝜋𝑛𝑘
𝑁
=α𝑋1 𝑘 + β𝑋2 𝑘
Hence proved
Circular Time Shifting
If 𝑥 𝑛 ↔ 𝑋 𝑘
then 𝑥(𝑛 − 𝑚) ↔= 𝑋 𝑘 𝑒−𝑗2𝜋𝑚𝑘
DFT is defined as 𝑋 𝑘 = 𝑛=0
𝑁−1
𝑥(𝑛)𝑒−
𝑗2𝜋𝑛𝑘
𝑁
=
𝑛=0
𝑁−1
𝑥(𝑛 − 𝑚)𝑒−
𝑗2𝜋𝑛𝑘
𝑁
Sub n-m=p, n=p+m
𝑋 𝑘 =
𝑝=0
𝑁−1
𝑥(𝑝)𝑒−
𝑗2𝜋(𝑝+𝑚)𝑘
𝑁
=
𝑝=0
𝑁−1
𝑥(𝑝)𝑒−
𝑗2𝜋𝑝𝑘
𝑁 𝑒−
𝑗2𝜋𝑚𝑘
𝑁
= 𝑒−
𝑗2𝜋𝑚𝑘
𝑁 𝑋 𝑘
Hence proved
Time Reversal property
If 𝑥 𝑛 ↔ 𝑋 𝑘
then 𝑥(−𝑛) ↔= 𝑋 −𝑘
DFT is defined as 𝑋 𝑘 = 𝑛=0
𝑁−1
𝑥(𝑛)𝑒−
𝑗2𝜋𝑛𝑘
𝑁
=
𝑛=0
𝑁−1
𝑥(−𝑛)𝑒−
𝑗2𝜋𝑛𝑘
𝑁
Sub –n=p
= 𝑝=0
𝑁−1
𝑥(𝑝)𝑒−
𝑗2𝜋(−𝑝)𝑘
𝑁
=
𝑝=0
𝑁−1
𝑥(𝑝)𝑒−
𝑗2𝜋𝑝(−𝑘)
𝑁
= 𝑋(−𝑘)
Hence Proved
Circular Convolution Property
If 𝑥1(𝑛) ↔ 𝑋𝑘 and 𝑥2 𝑛 ↔ 𝑋2 𝑘
then 𝑥1 𝑛 ∗ 𝑥2 𝑛 ↔ 𝑋1 𝑘 . 𝑋2 𝑘
DFT is defined as 𝑋 𝑘 = 𝑛=0
𝑁−1
𝑥(𝑛)𝑒−
𝑗2𝜋𝑛𝑘
𝑁
=
𝑛=0
𝑁−1
𝑥1 𝑛 ∗ 𝑥2 𝑛 ]𝑒−
𝑗2𝜋𝑛𝑘
𝑁
=
𝑛=0
𝑁−1
𝑚=0
𝑁−1
𝑥1 𝑚 𝑥2(𝑛 − 𝑚) 𝑒−
𝑗2𝜋𝑛𝑘
𝑁
[𝑥1 𝑛 ∗ 𝑥2 𝑛 = 𝑚=0
𝑁−1
𝑥1 𝑚 𝑥2 𝑛 − 𝑚 ]
Cond..
=
𝑚=0
𝑁−1
𝑥1(𝑚)
𝑛=0
𝑁−1
𝑥2(𝑛 − 𝑚) 𝑒−𝑗2𝜋𝑛𝑘/𝑁
= 𝑋2(k) 𝑚=0
𝑁−1
𝑥1(𝑚) 𝑒−𝑗2𝜋𝑚𝑘/𝑁
[using
time shift]
= 𝑋2 𝐾 𝑋1(𝐾)
Hence proved
Multiplication property
If 𝑥1(𝑛) ↔ 𝑋1(𝐾) and 𝑥2 𝑛 ↔ 𝑋2 𝑘
then 𝑥1 𝑛 𝑥2 𝑛 ↔ 1/𝑁[𝑋1 𝑘 ∗ 𝑋2 𝑘 ]
DFT is defined as 𝑋 𝑘 = 𝑛=0
𝑁−1
𝑥(𝑛)𝑒−
𝑗2𝜋𝑛𝑘
𝑁
=
𝑛=0
𝑁−1
𝑥1 𝑛 𝑥2 𝑛 𝑒−
𝑗2𝜋𝑛𝑘
𝑁
We know 𝑥1 𝑛 = 1/𝑁 𝑙=0
𝑁−1
𝑋1 𝑙 𝑒
𝑗2𝜋𝑛𝑙
𝑁
𝑋 𝑘 =
𝑛=0
𝑁−1
1/𝑁
𝑙=0
𝑁−1
𝑋1 𝑙 𝑒
𝑗2𝜋𝑛𝑙
𝑁 𝑥2 𝑛 𝑒−
𝑗2𝜋𝑛𝑘
𝑁
Cond..
=
1
𝑁
𝑙=0
𝑁−1
𝑋1(𝑙)
𝑛=0
𝑁−1
𝑥2(𝑛)𝑒−𝑗2𝜋𝑛(𝑘−𝑙)/𝑁
=
1
𝑁
𝑙=0
𝑁−1
𝑋1(𝑙)𝑋2(𝑘 − 𝑙)
=
1
𝑁
[𝑋1 𝑙 ∗ 𝑋2 𝑙 ]
=
1
𝑁
[𝑋1 𝑘 ∗ 𝑋2 𝑘 ]
Hence Proved.

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Transforms

  • 2. Need for Transform • Transforms make some types of calculations much simpler and more convenient. • Transforms are tools to make analysis easier. • Laplace transform, for example, makes solving differential equations easier. • Possible to do all computation and analysis of a signal in either the time domain or the frequency domain.
  • 4. Discrete Time Fourier Transform Pair          n n n j j e n x e X ) ( ) ( Analysis          d e e X n x n j j ) ( 2 1 ) ( Synthesis Inverse Fourier Transform (IFT) Fourier Transform (FT) )] ( [ ) ( n x e X j F   )] ( [ ) ( 1   j - e X n x F ) ( ) (    j e X n x F
  • 6. DFT
  • 8. DFT PROPERTIES Periodicity If 𝑥 𝑛 ↔ 𝑋 𝑘 𝑥(𝑛 + 𝑁) = 𝑥 𝑛 𝑓𝑜𝑟 𝑎𝑙𝑙 𝑛 𝑋 𝑘 + 𝑁 = 𝑋 𝑘 𝑓𝑜𝑟 𝑎𝑙𝑙 𝑘 DFT is defined as 𝑋 𝑘 = 𝑛=0 𝑁−1 𝑥(𝑛)𝑒− 𝑗2𝜋𝑛𝑘 𝑁 , 0≤𝑘≤𝑁−1 Sub k=k+N 𝑋 𝑘 + 𝑁 = 𝑛=0 𝑁−1 𝑥(𝑛)𝑒− 𝑗2𝜋𝑛(𝑘+𝑁) 𝑁
  • 9. Cond.. 𝑋 𝑘 + 𝑁 = 𝑛=0 𝑁−1 𝑥(𝑛)𝑒− 𝑗2𝜋𝑛𝑘 𝑁 𝑒− 𝑗2𝜋𝑛𝑁 𝑁 𝑋 𝑘 + 𝑁 = 𝑛=0 𝑁−1 𝑥(𝑛)𝑒− 𝑗2𝜋𝑛𝑘 𝑁 [𝑒−𝑗2𝜋𝑛 = 1] 𝑋 𝑘 + 𝑁 = 𝑋 𝑘 Hence Proved.
  • 10. Linearity • If 𝑥1 𝑛 ↔ 𝑋1 𝑘 𝑎𝑛𝑑 𝑥2 𝑛 ↔ 𝑋2 𝑘 Then ∝ 𝑥1 𝑛 + β𝑥2 𝑛 ↔ α𝑋1 𝑘 + β𝑋2 𝑘 DFT is defined as 𝑋 𝑘 = 𝑛=0 𝑁−1 𝑥(𝑛)𝑒− 𝑗2𝜋𝑛𝑘 𝑁 = 𝑛=0 𝑁−1 [∝ 𝑥1 𝑛 + β𝑥2 𝑛 ]𝑒− 𝑗2𝜋𝑛𝑘 𝑁 = 𝑛=0 𝑁−1 ∝ 𝑥1 𝑛 𝑒− 𝑗2𝜋𝑛𝑘 𝑁 + 𝑛=0 𝑁−1 β𝑥2 𝑛 𝑒− 𝑗2𝜋𝑛𝑘 𝑁 =∝ 𝑛=0 𝑁−1 𝑥1 𝑛 𝑒− 𝑗2𝜋𝑛𝑘 𝑁 + β 𝑛=0 𝑁−1 𝑥2 𝑛 𝑒− 𝑗2𝜋𝑛𝑘 𝑁 =α𝑋1 𝑘 + β𝑋2 𝑘 Hence proved
  • 11. Circular Time Shifting If 𝑥 𝑛 ↔ 𝑋 𝑘 then 𝑥(𝑛 − 𝑚) ↔= 𝑋 𝑘 𝑒−𝑗2𝜋𝑚𝑘 DFT is defined as 𝑋 𝑘 = 𝑛=0 𝑁−1 𝑥(𝑛)𝑒− 𝑗2𝜋𝑛𝑘 𝑁 = 𝑛=0 𝑁−1 𝑥(𝑛 − 𝑚)𝑒− 𝑗2𝜋𝑛𝑘 𝑁 Sub n-m=p, n=p+m 𝑋 𝑘 = 𝑝=0 𝑁−1 𝑥(𝑝)𝑒− 𝑗2𝜋(𝑝+𝑚)𝑘 𝑁 = 𝑝=0 𝑁−1 𝑥(𝑝)𝑒− 𝑗2𝜋𝑝𝑘 𝑁 𝑒− 𝑗2𝜋𝑚𝑘 𝑁 = 𝑒− 𝑗2𝜋𝑚𝑘 𝑁 𝑋 𝑘 Hence proved
  • 12. Time Reversal property If 𝑥 𝑛 ↔ 𝑋 𝑘 then 𝑥(−𝑛) ↔= 𝑋 −𝑘 DFT is defined as 𝑋 𝑘 = 𝑛=0 𝑁−1 𝑥(𝑛)𝑒− 𝑗2𝜋𝑛𝑘 𝑁 = 𝑛=0 𝑁−1 𝑥(−𝑛)𝑒− 𝑗2𝜋𝑛𝑘 𝑁 Sub –n=p = 𝑝=0 𝑁−1 𝑥(𝑝)𝑒− 𝑗2𝜋(−𝑝)𝑘 𝑁 = 𝑝=0 𝑁−1 𝑥(𝑝)𝑒− 𝑗2𝜋𝑝(−𝑘) 𝑁 = 𝑋(−𝑘) Hence Proved
  • 13. Circular Convolution Property If 𝑥1(𝑛) ↔ 𝑋𝑘 and 𝑥2 𝑛 ↔ 𝑋2 𝑘 then 𝑥1 𝑛 ∗ 𝑥2 𝑛 ↔ 𝑋1 𝑘 . 𝑋2 𝑘 DFT is defined as 𝑋 𝑘 = 𝑛=0 𝑁−1 𝑥(𝑛)𝑒− 𝑗2𝜋𝑛𝑘 𝑁 = 𝑛=0 𝑁−1 𝑥1 𝑛 ∗ 𝑥2 𝑛 ]𝑒− 𝑗2𝜋𝑛𝑘 𝑁 = 𝑛=0 𝑁−1 𝑚=0 𝑁−1 𝑥1 𝑚 𝑥2(𝑛 − 𝑚) 𝑒− 𝑗2𝜋𝑛𝑘 𝑁 [𝑥1 𝑛 ∗ 𝑥2 𝑛 = 𝑚=0 𝑁−1 𝑥1 𝑚 𝑥2 𝑛 − 𝑚 ]
  • 14. Cond.. = 𝑚=0 𝑁−1 𝑥1(𝑚) 𝑛=0 𝑁−1 𝑥2(𝑛 − 𝑚) 𝑒−𝑗2𝜋𝑛𝑘/𝑁 = 𝑋2(k) 𝑚=0 𝑁−1 𝑥1(𝑚) 𝑒−𝑗2𝜋𝑚𝑘/𝑁 [using time shift] = 𝑋2 𝐾 𝑋1(𝐾) Hence proved
  • 15. Multiplication property If 𝑥1(𝑛) ↔ 𝑋1(𝐾) and 𝑥2 𝑛 ↔ 𝑋2 𝑘 then 𝑥1 𝑛 𝑥2 𝑛 ↔ 1/𝑁[𝑋1 𝑘 ∗ 𝑋2 𝑘 ] DFT is defined as 𝑋 𝑘 = 𝑛=0 𝑁−1 𝑥(𝑛)𝑒− 𝑗2𝜋𝑛𝑘 𝑁 = 𝑛=0 𝑁−1 𝑥1 𝑛 𝑥2 𝑛 𝑒− 𝑗2𝜋𝑛𝑘 𝑁 We know 𝑥1 𝑛 = 1/𝑁 𝑙=0 𝑁−1 𝑋1 𝑙 𝑒 𝑗2𝜋𝑛𝑙 𝑁 𝑋 𝑘 = 𝑛=0 𝑁−1 1/𝑁 𝑙=0 𝑁−1 𝑋1 𝑙 𝑒 𝑗2𝜋𝑛𝑙 𝑁 𝑥2 𝑛 𝑒− 𝑗2𝜋𝑛𝑘 𝑁