मुक्त ज्ञानकोश विकिपीडिया से
गणित में डिस्क्रीट टाइम फुरिअर ट्रान्सफार्म या डीटीएफटी (discrete-time Fourier transform or DTFT ), फुरिअर विश्लेषण के कई रुपों में से एक रूप है। यह अनन्त तक परिभाषित किसी अनावर्ती (नॉन्-पेरिऑडिक) डिस्क्रीट-टाइम सेक्वेंस को रूपानतरित करता है। इसे यह भी कहते हैं कि समय-डोमेन का आंकड़ा आवृत्ति-डोमेन में बदल गया। डीटीएफटी द्वारा प्राप्त आवृत्ति-डोमेन का आंकड़ा सतत (कांटिन्युअस) एवं आवर्ती होता है।
यदि कोई वास्तविक (real) या समिश्र (complex) संख्याओं का समुच्चय :
x
[
n
]
,
n
∈
Z
{\displaystyle x[n],\;n\in \mathbb {Z} }
(पूर्णांक ), दिया हो तो
x
[
n
]
{\displaystyle x[n]\,}
का डीटीएफटी प्रायः इस प्रकार व्यक्त किया जाता है:
X
(
ω
)
=
∑
n
=
−
∞
∞
x
[
n
]
e
−
i
ω
n
.
{\displaystyle X(\omega )=\sum _{n=-\infty }^{\infty }x[n]\,e^{-i\omega n}.}
निम्नलिखित रुपान्तर करने पर डिस्क्रीट-टाइम सेक्वेंस फिर से प्राप्त हो जायेगा:
x
[
n
]
{\displaystyle x[n]\,}
=
1
2
π
∫
−
π
π
X
(
ω
)
⋅
e
i
ω
n
d
ω
{\displaystyle ={\frac {1}{2\pi }}\int _{-\pi }^{\pi }X(\omega )\cdot e^{i\omega n}\,d\omega }
=
T
∫
−
1
2
T
1
2
T
X
T
(
f
)
⋅
e
i
2
π
f
n
T
d
f
.
{\displaystyle =T\int _{-{\frac {1}{2T}}}^{\frac {1}{2T}}X_{T}(f)\cdot e^{i2\pi fnT}\,df.}
The integrals span one full period of the DTFT, which means that the x[n] samples are also the coefficients of a Fourier series expansion of the DTFT. Infinite limits of integration change the transform into a continuous-time Fourier transform [inverse], which produces a sequence of Dirac impulses. That is:
∫
−
∞
∞
X
T
(
f
)
⋅
e
i
2
π
f
t
d
f
=
∫
−
∞
∞
(
T
∑
n
=
−
∞
∞
x
(
n
T
)
e
−
i
2
π
f
T
n
)
⋅
e
i
2
π
f
t
d
f
=
∑
n
=
−
∞
∞
T
⋅
x
(
n
T
)
∫
−
∞
∞
e
−
i
2
π
f
T
n
⋅
e
i
2
π
f
t
d
f
=
∑
n
=
−
∞
∞
x
[
n
]
⋅
δ
(
t
−
n
T
)
.
{\displaystyle {\begin{aligned}\int _{-\infty }^{\infty }X_{T}(f)\cdot e^{i2\pi ft}\,df&=\int _{-\infty }^{\infty }\left(T\sum _{n=-\infty }^{\infty }x(nT)\ e^{-i2\pi fTn}\right)\cdot e^{i2\pi ft}\,df\\&=\sum _{n=-\infty }^{\infty }T\cdot x(nT)\int _{-\infty }^{\infty }e^{-i2\pi fTn}\cdot e^{i2\pi ft}\,df\\&=\sum _{n=-\infty }^{\infty }x[n]\cdot \delta (t-nT).\end{aligned}}}
नीचे कुछ मानक डिस्क्रीट टाइम सेक्वेंस एवं उनके डीटीएफटी रुपानतर दिये हुए हैं। इसमें प्रयुक्त प्रतीकों का अर्थ निम्नवत है:
n
{\displaystyle n\!}
is an integer representing the discrete-time domain (in samples)
ω
{\displaystyle \omega \!}
is a real number in
(
−
π
,
π
)
{\displaystyle (-\pi ,\ \pi )}
, representing continuous angular frequency (in radians per sample).
The remainder of the transform
(
|
ω
|
>
π
)
{\displaystyle (|\omega |>\pi \,)}
is defined by:
X
(
ω
+
2
π
k
)
=
X
(
ω
)
{\displaystyle X(\omega +2\pi k)=X(\omega )\,}
u
[
n
]
{\displaystyle u[n]\!}
is the discrete-time unit step function
sinc
(
t
)
{\displaystyle \operatorname {sinc} (t)\!}
is the normalized sinc function
δ
(
ω
)
{\displaystyle \delta (\omega )\!}
is the Dirac delta function
δ
[
n
]
{\displaystyle \delta [n]\!}
is the Kronecker delta
δ
n
,
0
{\displaystyle \delta _{n,0}\!}
rect
(
t
)
{\displaystyle \operatorname {rect} (t)}
is the rectangle function for arbitrary real-valued t :
r
e
c
t
(
t
)
=
⊓
(
t
)
=
{
0
if
|
t
|
>
1
2
1
2
if
|
t
|
=
1
2
1
if
|
t
|
<
1
2
{\displaystyle \mathrm {rect} (t)=\sqcap (t)={\begin{cases}0&{\mbox{if }}|t|>{\frac {1}{2}}\\[3pt]{\frac {1}{2}}&{\mbox{if }}|t|={\frac {1}{2}}\\[3pt]1&{\mbox{if }}|t|<{\frac {1}{2}}\end{cases}}}
tri
(
t
)
{\displaystyle \operatorname {tri} (t)}
is the triangle function for arbitrary real-valued t :
tri
(
t
)
=
∧
(
t
)
=
{
1
+
t
;
−
1
≤
t
≤
0
1
−
t
;
0
<
t
≤
1
0
otherwise
{\displaystyle \operatorname {tri} (t)=\land (t)={\begin{cases}1+t;&-1\leq t\leq 0\\1-t;&0<t\leq 1\\0&{\mbox{otherwise}}\end{cases}}}
Time domain
x
[
n
]
{\displaystyle x[n]\,}
Frequency domain
X
(
ω
)
{\displaystyle X(\omega )\,}
Remarks
δ
[
n
]
{\displaystyle \delta [n]\!}
1
{\displaystyle 1\!}
δ
[
n
−
M
]
{\displaystyle \delta [n-M]\!}
e
−
i
ω
M
{\displaystyle e^{-i\omega M}\!}
integer M
∑
m
=
−
∞
∞
δ
[
n
−
M
m
]
{\displaystyle \sum _{m=-\infty }^{\infty }\delta [n-Mm]\,}
∑
m
=
−
∞
∞
e
−
i
ω
M
m
=
1
M
∑
k
=
−
∞
∞
δ
(
ω
2
π
−
k
M
)
{\displaystyle \sum _{m=-\infty }^{\infty }e^{-i\omega Mm}={\frac {1}{M}}\sum _{k=-\infty }^{\infty }\delta \left({\frac {\omega }{2\pi }}-{\frac {k}{M}}\right)\,}
integer M
u
[
n
]
{\displaystyle u[n]\!}
1
1
−
e
−
i
ω
{\displaystyle {\frac {1}{1-e^{-i\omega }}}\!}
e
−
i
a
n
{\displaystyle e^{-ian}\!}
2
π
δ
(
ω
+
a
)
{\displaystyle 2\pi \delta (\omega +a)\,}
real number a
cos
(
a
n
)
{\displaystyle \cos(an)\!}
π
[
δ
(
ω
−
a
)
+
δ
(
ω
+
a
)
]
{\displaystyle \pi \left[\delta (\omega -a)+\delta (\omega +a)\right]}
real number a
sin
(
a
n
)
{\displaystyle \sin(an)\!}
π
i
[
δ
(
ω
−
a
)
−
δ
(
ω
+
a
)
]
{\displaystyle {\frac {\pi }{i}}\left[\delta (\omega -a)-\delta (\omega +a)\right]}
real number a
r
e
c
t
[
(
n
−
M
/
2
)
M
]
{\displaystyle \mathrm {rect} \left[{(n-M/2) \over M}\right]}
sin
[
ω
(
M
+
1
)
/
2
]
sin
(
ω
/
2
)
e
−
i
ω
M
/
2
{\displaystyle {\sin[\omega (M+1)/2] \over \sin(\omega /2)}\,e^{-i\omega M/2}}
integer M
sinc
[
(
a
+
n
)
]
{\displaystyle \operatorname {sinc} [(a+n)]}
e
i
a
ω
{\displaystyle e^{ia\omega }\!}
real number a
W
⋅
sinc
2
(
W
n
)
{\displaystyle W\cdot \operatorname {sinc} ^{2}(Wn)\,}
tri
(
ω
2
π
W
)
{\displaystyle \operatorname {tri} \left({\omega \over 2\pi W}\right)}
real number W
0
<
W
≤
0.5
{\displaystyle 0<W\leq 0.5}
W
⋅
sinc
[
W
(
n
+
a
)
]
{\displaystyle W\cdot \operatorname {sinc} [W(n+a)]}
rect
(
ω
2
π
W
)
⋅
e
j
a
ω
{\displaystyle \operatorname {rect} \left({\omega \over 2\pi W}\right)\cdot e^{ja\omega }}
real numbers W , a
0
<
W
≤
1
{\displaystyle 0<W\leq 1}
{
0
n
=
0
(
−
1
)
n
n
elsewhere
{\displaystyle {\begin{cases}0&n=0\\{\frac {(-1)^{n}}{n}}&{\mbox{elsewhere}}\end{cases}}}
j
ω
{\displaystyle j\omega }
it works as a differentiator filter
W
(
n
+
a
)
{
cos
[
π
W
(
n
+
a
)
]
−
sinc
[
W
(
n
+
a
)
]
}
{\displaystyle {\frac {W}{(n+a)}}\left\{\cos[\pi W(n+a)]-\operatorname {sinc} [W(n+a)]\right\}}
j
ω
⋅
rect
(
ω
π
W
)
e
j
a
ω
{\displaystyle j\omega \cdot \operatorname {rect} \left({\omega \over \pi W}\right)e^{ja\omega }}
real numbers W , a
0
<
W
≤
1
{\displaystyle 0<W\leq 1}
1
π
n
2
[
(
−
1
)
n
−
1
]
{\displaystyle {\frac {1}{\pi n^{2}}}[(-1)^{n}-1]}
|
ω
|
{\displaystyle |\omega |\!}
{
0
;
n
odd
2
π
n
;
n
even
{\displaystyle {\begin{cases}0;&n{\mbox{ odd}}\\{\frac {2}{\pi n}};&n{\mbox{ even}}\end{cases}}}
{
j
ω
<
0
0
ω
=
0
−
j
ω
>
0
{\displaystyle {\begin{cases}j&\omega <0\\0&\omega =0\\-j&\omega >0\end{cases}}}
Hilbert transform
C
(
A
+
B
)
2
π
⋅
sinc
[
A
−
B
2
π
n
]
⋅
sinc
[
A
+
B
2
π
n
]
{\displaystyle {\frac {C(A+B)}{2\pi }}\cdot \operatorname {sinc} \left[{\frac {A-B}{2\pi }}n\right]\cdot \operatorname {sinc} \left[{\frac {A+B}{2\pi }}n\right]}
real numbers A , B complex C
This table shows the relationships between generic discrete-time Fourier transforms.
We use the following notation:
∗
{\displaystyle *\!}
is the convolution between two signals
x
[
n
]
∗
{\displaystyle x[n]^{*}\!}
is the complex conjugate of the function x[n]
ρ
x
y
[
n
]
{\displaystyle \rho _{xy}[n]\!}
represents the correlation between x[n] and y[n] .
The first column provides a description of the property, the second column shows the function in the time domain, the third column shows the spectrum in the frequency domain:
Property
Time domain
x
[
n
]
{\displaystyle x[n]\!}
Frequency domain
X
(
ω
)
{\displaystyle X(\omega )\!}
Remarks
Linearity
a
x
[
n
]
+
b
y
[
n
]
{\displaystyle ax[n]+by[n]\!}
a
X
(
e
i
ω
)
+
b
Y
(
e
i
ω
)
{\displaystyle aX(e^{i\omega })+bY(e^{i\omega })\!}
Shift in time
x
[
n
−
k
]
{\displaystyle x[n-k]\!}
X
(
e
i
ω
)
e
−
i
ω
k
{\displaystyle X(e^{i\omega })e^{-i\omega k}\!}
integer k
Shift in frequency (modulation)
x
[
n
]
e
i
a
n
{\displaystyle x[n]e^{ian}\!}
X
(
e
i
(
ω
−
a
)
)
{\displaystyle X(e^{i(\omega -a)})\!}
real number a
Time reversal
x
[
−
n
]
{\displaystyle x[-n]\!}
X
(
e
−
i
ω
)
{\displaystyle X(e^{-i\omega })\!}
Time conjugation
x
[
n
]
∗
{\displaystyle x[n]^{*}\!}
X
(
e
−
i
ω
)
∗
{\displaystyle X(e^{-i\omega })^{*}\!}
Time reversal & conjugation
x
[
−
n
]
∗
{\displaystyle x[-n]^{*}\!}
X
(
e
i
ω
)
∗
{\displaystyle X(e^{i\omega })^{*}\!}
Derivative in frequency
n
i
x
[
n
]
{\displaystyle {\frac {n}{i}}x[n]\!}
d
X
(
e
i
ω
)
d
ω
{\displaystyle {\frac {dX(e^{i\omega })}{d\omega }}\!}
Integral in frequency
i
n
x
[
n
]
{\displaystyle {\frac {i}{n}}x[n]\!}
∫
−
π
ω
X
(
e
i
ϑ
)
d
ϑ
{\displaystyle \int _{-\pi }^{\omega }X(e^{i\vartheta })d\vartheta \!}
Convolve in time
x
[
n
]
∗
y
[
n
]
{\displaystyle x[n]*y[n]\!}
X
(
e
i
ω
)
⋅
Y
(
e
i
ω
)
{\displaystyle X(e^{i\omega })\cdot Y(e^{i\omega })\!}
Multiply in time
x
[
n
]
⋅
y
[
n
]
{\displaystyle x[n]\cdot y[n]\!}
1
2
π
X
(
e
i
ω
)
∗
Y
(
e
i
ω
)
{\displaystyle {\frac {1}{2\pi }}X(e^{i\omega })*Y(e^{i\omega })\!}
Correlation
ρ
x
y
[
n
]
=
x
[
−
n
]
∗
∗
y
[
n
]
{\displaystyle \rho _{xy}[n]=x[-n]^{*}*y[n]\!}
R
x
y
(
ω
)
=
X
(
e
i
ω
)
∗
⋅
Y
(
e
i
ω
)
{\displaystyle R_{xy}(\omega )=X(e^{i\omega })^{*}\cdot Y(e^{i\omega })\!}
फुरिअर रुपान्तर, वास्तविक एवं काल्पनिक (real and imaginary) या सम एवं विषम (even and odd) के योग के रूप में व्यक्त की जा सकती है।
X
(
e
i
ω
)
=
X
R
(
e
i
ω
)
+
i
X
I
(
e
i
ω
)
{\displaystyle X(e^{i\omega })=X_{R}(e^{i\omega })+iX_{I}(e^{i\omega })\!}
या
X
(
e
i
ω
)
=
X
E
(
e
i
ω
)
+
X
O
(
e
i
ω
)
{\displaystyle X(e^{i\omega })=X_{E}(e^{i\omega })+X_{O}(e^{i\omega })\!}
Time Domain
x
[
n
]
{\displaystyle x[n]\!}
Frequency Domain
X
(
e
i
ω
)
{\displaystyle X(e^{i\omega })\!}
x
∗
[
n
]
{\displaystyle x^{*}[n]\!}
X
∗
(
e
−
i
ω
)
{\displaystyle X^{*}(e^{-i\omega })\!}
x
∗
[
−
n
]
{\displaystyle x^{*}[-n]\!}
X
∗
(
e
i
ω
)
{\displaystyle X^{*}(e^{i\omega })\!}