The Fourier transform of a “comb function” is a comb function?

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Let $f(x) = sum_n=-infty^infty delta(x - n)$, where $delta$ is the Dirac delta function. This function $f$ (a "comb function") is important in signal processing because evenly sampling a function $g$ can be viewed as multiplying $g$ pointwise with $f$. This idea is the first step towards understanding how to approximate the Fourier transform of $g$, given evenly spaced samples of $g$. The next step is to note that $hatgf = hatg*hatf$, where $hatf$ is the Fourier transform of $f$ and $*$ denotes convolution.



Is it true that $hat f$ is also a comb function? If that statement isn't quite right, what is the correct statement?



I would like to see: 1) an informal, intuitive, nonrigorous but easy derivation of the Fourier transform of $f$ . 2) A rigorous version of the same calculation. (How would you even define $f$ rigorously, is it a distribution?)



(I'd also be interested in recommendations of math textbooks that cover this topic, including the Nyquist sampling theorem, even if it's only an exercise or series of exercises in an analysis textbook.)










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  • 3




    The following should be helpful: mathoverflow.net/questions/14568/…
    – Justthisguy
    Aug 20 '16 at 22:12






  • 2




    Intuitively: The Fourier coefficient at frequency $omega$ is nonzero iff the sinusoid $e^ixomega$ lines up with the "teeth" of the comb.
    – Rahul
    Aug 22 '16 at 23:29







  • 2




    en.wikipedia.org/wiki/Dirac_comb#Fourier_series
    – rikhavshah
    Aug 22 '16 at 23:56










  • If I remember correctly from fifty years ago, the only function that is its own fourier transform is the bell curve. For the discrete case, it would be the binomial coefficients (which approach the bell curve when there are many of them). Important in antenna design and optics apodizing.
    – richard1941
    Aug 24 '16 at 21:12






  • 3




    @richard1941 it is not true that the Bell curve is the only function that is its own fourier transform. As you can see here, the Bell curve times a Hermite polynomial of order $4 n$ is also invariant under Fourier transformation.
    – Fabian
    Aug 29 '16 at 21:19














up vote
10
down vote

favorite
3












Let $f(x) = sum_n=-infty^infty delta(x - n)$, where $delta$ is the Dirac delta function. This function $f$ (a "comb function") is important in signal processing because evenly sampling a function $g$ can be viewed as multiplying $g$ pointwise with $f$. This idea is the first step towards understanding how to approximate the Fourier transform of $g$, given evenly spaced samples of $g$. The next step is to note that $hatgf = hatg*hatf$, where $hatf$ is the Fourier transform of $f$ and $*$ denotes convolution.



Is it true that $hat f$ is also a comb function? If that statement isn't quite right, what is the correct statement?



I would like to see: 1) an informal, intuitive, nonrigorous but easy derivation of the Fourier transform of $f$ . 2) A rigorous version of the same calculation. (How would you even define $f$ rigorously, is it a distribution?)



(I'd also be interested in recommendations of math textbooks that cover this topic, including the Nyquist sampling theorem, even if it's only an exercise or series of exercises in an analysis textbook.)










share|cite|improve this question



















  • 3




    The following should be helpful: mathoverflow.net/questions/14568/…
    – Justthisguy
    Aug 20 '16 at 22:12






  • 2




    Intuitively: The Fourier coefficient at frequency $omega$ is nonzero iff the sinusoid $e^ixomega$ lines up with the "teeth" of the comb.
    – Rahul
    Aug 22 '16 at 23:29







  • 2




    en.wikipedia.org/wiki/Dirac_comb#Fourier_series
    – rikhavshah
    Aug 22 '16 at 23:56










  • If I remember correctly from fifty years ago, the only function that is its own fourier transform is the bell curve. For the discrete case, it would be the binomial coefficients (which approach the bell curve when there are many of them). Important in antenna design and optics apodizing.
    – richard1941
    Aug 24 '16 at 21:12






  • 3




    @richard1941 it is not true that the Bell curve is the only function that is its own fourier transform. As you can see here, the Bell curve times a Hermite polynomial of order $4 n$ is also invariant under Fourier transformation.
    – Fabian
    Aug 29 '16 at 21:19












up vote
10
down vote

favorite
3









up vote
10
down vote

favorite
3






3





Let $f(x) = sum_n=-infty^infty delta(x - n)$, where $delta$ is the Dirac delta function. This function $f$ (a "comb function") is important in signal processing because evenly sampling a function $g$ can be viewed as multiplying $g$ pointwise with $f$. This idea is the first step towards understanding how to approximate the Fourier transform of $g$, given evenly spaced samples of $g$. The next step is to note that $hatgf = hatg*hatf$, where $hatf$ is the Fourier transform of $f$ and $*$ denotes convolution.



Is it true that $hat f$ is also a comb function? If that statement isn't quite right, what is the correct statement?



I would like to see: 1) an informal, intuitive, nonrigorous but easy derivation of the Fourier transform of $f$ . 2) A rigorous version of the same calculation. (How would you even define $f$ rigorously, is it a distribution?)



(I'd also be interested in recommendations of math textbooks that cover this topic, including the Nyquist sampling theorem, even if it's only an exercise or series of exercises in an analysis textbook.)










share|cite|improve this question















Let $f(x) = sum_n=-infty^infty delta(x - n)$, where $delta$ is the Dirac delta function. This function $f$ (a "comb function") is important in signal processing because evenly sampling a function $g$ can be viewed as multiplying $g$ pointwise with $f$. This idea is the first step towards understanding how to approximate the Fourier transform of $g$, given evenly spaced samples of $g$. The next step is to note that $hatgf = hatg*hatf$, where $hatf$ is the Fourier transform of $f$ and $*$ denotes convolution.



Is it true that $hat f$ is also a comb function? If that statement isn't quite right, what is the correct statement?



I would like to see: 1) an informal, intuitive, nonrigorous but easy derivation of the Fourier transform of $f$ . 2) A rigorous version of the same calculation. (How would you even define $f$ rigorously, is it a distribution?)



(I'd also be interested in recommendations of math textbooks that cover this topic, including the Nyquist sampling theorem, even if it's only an exercise or series of exercises in an analysis textbook.)







fourier-analysis






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edited Aug 20 '16 at 21:50

























asked Aug 20 '16 at 21:31









littleO

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  • 3




    The following should be helpful: mathoverflow.net/questions/14568/…
    – Justthisguy
    Aug 20 '16 at 22:12






  • 2




    Intuitively: The Fourier coefficient at frequency $omega$ is nonzero iff the sinusoid $e^ixomega$ lines up with the "teeth" of the comb.
    – Rahul
    Aug 22 '16 at 23:29







  • 2




    en.wikipedia.org/wiki/Dirac_comb#Fourier_series
    – rikhavshah
    Aug 22 '16 at 23:56










  • If I remember correctly from fifty years ago, the only function that is its own fourier transform is the bell curve. For the discrete case, it would be the binomial coefficients (which approach the bell curve when there are many of them). Important in antenna design and optics apodizing.
    – richard1941
    Aug 24 '16 at 21:12






  • 3




    @richard1941 it is not true that the Bell curve is the only function that is its own fourier transform. As you can see here, the Bell curve times a Hermite polynomial of order $4 n$ is also invariant under Fourier transformation.
    – Fabian
    Aug 29 '16 at 21:19












  • 3




    The following should be helpful: mathoverflow.net/questions/14568/…
    – Justthisguy
    Aug 20 '16 at 22:12






  • 2




    Intuitively: The Fourier coefficient at frequency $omega$ is nonzero iff the sinusoid $e^ixomega$ lines up with the "teeth" of the comb.
    – Rahul
    Aug 22 '16 at 23:29







  • 2




    en.wikipedia.org/wiki/Dirac_comb#Fourier_series
    – rikhavshah
    Aug 22 '16 at 23:56










  • If I remember correctly from fifty years ago, the only function that is its own fourier transform is the bell curve. For the discrete case, it would be the binomial coefficients (which approach the bell curve when there are many of them). Important in antenna design and optics apodizing.
    – richard1941
    Aug 24 '16 at 21:12






  • 3




    @richard1941 it is not true that the Bell curve is the only function that is its own fourier transform. As you can see here, the Bell curve times a Hermite polynomial of order $4 n$ is also invariant under Fourier transformation.
    – Fabian
    Aug 29 '16 at 21:19







3




3




The following should be helpful: mathoverflow.net/questions/14568/…
– Justthisguy
Aug 20 '16 at 22:12




The following should be helpful: mathoverflow.net/questions/14568/…
– Justthisguy
Aug 20 '16 at 22:12




2




2




Intuitively: The Fourier coefficient at frequency $omega$ is nonzero iff the sinusoid $e^ixomega$ lines up with the "teeth" of the comb.
– Rahul
Aug 22 '16 at 23:29





Intuitively: The Fourier coefficient at frequency $omega$ is nonzero iff the sinusoid $e^ixomega$ lines up with the "teeth" of the comb.
– Rahul
Aug 22 '16 at 23:29





2




2




en.wikipedia.org/wiki/Dirac_comb#Fourier_series
– rikhavshah
Aug 22 '16 at 23:56




en.wikipedia.org/wiki/Dirac_comb#Fourier_series
– rikhavshah
Aug 22 '16 at 23:56












If I remember correctly from fifty years ago, the only function that is its own fourier transform is the bell curve. For the discrete case, it would be the binomial coefficients (which approach the bell curve when there are many of them). Important in antenna design and optics apodizing.
– richard1941
Aug 24 '16 at 21:12




If I remember correctly from fifty years ago, the only function that is its own fourier transform is the bell curve. For the discrete case, it would be the binomial coefficients (which approach the bell curve when there are many of them). Important in antenna design and optics apodizing.
– richard1941
Aug 24 '16 at 21:12




3




3




@richard1941 it is not true that the Bell curve is the only function that is its own fourier transform. As you can see here, the Bell curve times a Hermite polynomial of order $4 n$ is also invariant under Fourier transformation.
– Fabian
Aug 29 '16 at 21:19




@richard1941 it is not true that the Bell curve is the only function that is its own fourier transform. As you can see here, the Bell curve times a Hermite polynomial of order $4 n$ is also invariant under Fourier transformation.
– Fabian
Aug 29 '16 at 21:19










3 Answers
3






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oldest

votes

















up vote
9
down vote



accepted
+50










Assume an arbitrary periodic function $f(t)$ with period $T$. Consider the Fourier series representation of $f(t)$, in which $omega_0=frac2piT$:
$$f(t)=sum_n=-infty^+inftyc_n e^i n omega_0 t$$
Take the Fourier transform of the sides:
beginalign
mathcalFf(t)=&mathcalFsum_n=-infty^+inftyc_n e^i n omega_0 t\
=&sum_n=-infty^+inftyc_nmathcalF e^i n omega_0 t\
F(omega)=&2pisum_n=-infty^+inftyc_ndelta(omega-nomega_0)
endalign
This means that the Fourier transform of a periodic signal is an impulse train where the impulse amplitudes are $2pi$ times the Fourier coefficients of that signal.



With $f(t)=delta(t)$, the Fourier series coefficients are $c_n=frac1T$ for all $n$.



Hence,
$$mathcalFsum_n=-infty^+inftydelta(t-nT)=frac2piT sum_n=-infty^+inftydelta(omega-nomega_0)$$
or in comb notation:
$$boxedmathcalFtextcomb_T(t)=omega_0 textcomb_omega_0(omega)$$



where
$$textcomb_A(x)triangleqsum_n=-infty^+inftydelta(x-nA)$$






share|cite|improve this answer






















  • Thanks, this is great. Do you recommend any books for this topic? Can you elaborate on how you compute the Fourier transform of $e^j n omega_0 t$?
    – littleO
    Aug 28 '16 at 0:17










  • The content can be found on most relevant books. However, if you look at signal processing textbooks you may find similar topics. The Fourier transform of $e^jnomega_0t$ can be found simply by recalling the "frequency shifting" property of Fourier transform, that is : $mathcalFe^jnomega_0tg(t)=G(omega-nomega_0)$ and the fact that $mathcalF1=2pidelta(omega)$.
    – msm
    Aug 28 '16 at 1:41






  • 1




    In order to get to $mathcalF1=2pidelta(omega)$ itself, one needs to accept $mathcalFdelta(t)=1$ and then use the "duality" property of Fourier transform that is : $mathcalFF(-t)=2pi f(omega)$. If you are interested in why $mathcalFdelta(t)=1$ as well, assume a form of pulse such as Gaussian, triangle, rectangle, etc. in the time domain and limit the pulse width to zero (i.e. $delta(t)$). You will get a frequency representation that expands more and more and tends to a constant in limit.
    – msm
    Aug 28 '16 at 2:57











  • Shouldn't the Fourier coefficients for $operatornamecomb_T (t)$ be $frac2T$, since we have $$frac1T int_0^T operatornamecomb_T (t) e^-jnomega_0 t operatornamedt = frac1T int_0^T big( delta(t) + delta(t-T) big) operatornamedt ?$$ This leads to an extra factor $2$ in your Fourier Transform of the comb function.
    – Mussé Redi
    Jun 2 at 15:22







  • 1




    I'm using the convention $$f(t) = frac12pi int_-infty^infty F(omega)e^iomega t operatornamedt .$$ Which convention are you using?
    – Mussé Redi
    Jun 2 at 15:28

















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3
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Intuitive Explanation



The Comb is a sum of Time Shifted Dirac Delta.



The Fourier Transform of a Dirac Delta is known to be a constant.



The Fourier Transform of a Time Shifted Function is known to be Fourier Transform of the function multiplied by a complex exponential factor which is $ exp(-i 2 pi f T) $



Just apply this points to the Comb Function considered as a sum of Time Shifted Dirac Delta with distance $ kT $ and you get a sum of Frequency Shifted exponential functions, each of which multiplied by a constant.



Finally use Euler’s Formula to consider complex exponentials as a periodic sinusoidal function and observe that you have constructive interference only in frequencies which are integer multiple of $ frac1T $






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    Up to constants and normalizations, this Dirac comb is its own Fourier transform: the assertion of this evaluated on (for example) a Schwartz function, $sum_nin mathbb Z f(n) ;=; sum_ninmathbb Z widehatf(n)$, is the Poisson summation formula.






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      3 Answers
      3






      active

      oldest

      votes








      3 Answers
      3






      active

      oldest

      votes









      active

      oldest

      votes






      active

      oldest

      votes








      up vote
      9
      down vote



      accepted
      +50










      Assume an arbitrary periodic function $f(t)$ with period $T$. Consider the Fourier series representation of $f(t)$, in which $omega_0=frac2piT$:
      $$f(t)=sum_n=-infty^+inftyc_n e^i n omega_0 t$$
      Take the Fourier transform of the sides:
      beginalign
      mathcalFf(t)=&mathcalFsum_n=-infty^+inftyc_n e^i n omega_0 t\
      =&sum_n=-infty^+inftyc_nmathcalF e^i n omega_0 t\
      F(omega)=&2pisum_n=-infty^+inftyc_ndelta(omega-nomega_0)
      endalign
      This means that the Fourier transform of a periodic signal is an impulse train where the impulse amplitudes are $2pi$ times the Fourier coefficients of that signal.



      With $f(t)=delta(t)$, the Fourier series coefficients are $c_n=frac1T$ for all $n$.



      Hence,
      $$mathcalFsum_n=-infty^+inftydelta(t-nT)=frac2piT sum_n=-infty^+inftydelta(omega-nomega_0)$$
      or in comb notation:
      $$boxedmathcalFtextcomb_T(t)=omega_0 textcomb_omega_0(omega)$$



      where
      $$textcomb_A(x)triangleqsum_n=-infty^+inftydelta(x-nA)$$






      share|cite|improve this answer






















      • Thanks, this is great. Do you recommend any books for this topic? Can you elaborate on how you compute the Fourier transform of $e^j n omega_0 t$?
        – littleO
        Aug 28 '16 at 0:17










      • The content can be found on most relevant books. However, if you look at signal processing textbooks you may find similar topics. The Fourier transform of $e^jnomega_0t$ can be found simply by recalling the "frequency shifting" property of Fourier transform, that is : $mathcalFe^jnomega_0tg(t)=G(omega-nomega_0)$ and the fact that $mathcalF1=2pidelta(omega)$.
        – msm
        Aug 28 '16 at 1:41






      • 1




        In order to get to $mathcalF1=2pidelta(omega)$ itself, one needs to accept $mathcalFdelta(t)=1$ and then use the "duality" property of Fourier transform that is : $mathcalFF(-t)=2pi f(omega)$. If you are interested in why $mathcalFdelta(t)=1$ as well, assume a form of pulse such as Gaussian, triangle, rectangle, etc. in the time domain and limit the pulse width to zero (i.e. $delta(t)$). You will get a frequency representation that expands more and more and tends to a constant in limit.
        – msm
        Aug 28 '16 at 2:57











      • Shouldn't the Fourier coefficients for $operatornamecomb_T (t)$ be $frac2T$, since we have $$frac1T int_0^T operatornamecomb_T (t) e^-jnomega_0 t operatornamedt = frac1T int_0^T big( delta(t) + delta(t-T) big) operatornamedt ?$$ This leads to an extra factor $2$ in your Fourier Transform of the comb function.
        – Mussé Redi
        Jun 2 at 15:22







      • 1




        I'm using the convention $$f(t) = frac12pi int_-infty^infty F(omega)e^iomega t operatornamedt .$$ Which convention are you using?
        – Mussé Redi
        Jun 2 at 15:28














      up vote
      9
      down vote



      accepted
      +50










      Assume an arbitrary periodic function $f(t)$ with period $T$. Consider the Fourier series representation of $f(t)$, in which $omega_0=frac2piT$:
      $$f(t)=sum_n=-infty^+inftyc_n e^i n omega_0 t$$
      Take the Fourier transform of the sides:
      beginalign
      mathcalFf(t)=&mathcalFsum_n=-infty^+inftyc_n e^i n omega_0 t\
      =&sum_n=-infty^+inftyc_nmathcalF e^i n omega_0 t\
      F(omega)=&2pisum_n=-infty^+inftyc_ndelta(omega-nomega_0)
      endalign
      This means that the Fourier transform of a periodic signal is an impulse train where the impulse amplitudes are $2pi$ times the Fourier coefficients of that signal.



      With $f(t)=delta(t)$, the Fourier series coefficients are $c_n=frac1T$ for all $n$.



      Hence,
      $$mathcalFsum_n=-infty^+inftydelta(t-nT)=frac2piT sum_n=-infty^+inftydelta(omega-nomega_0)$$
      or in comb notation:
      $$boxedmathcalFtextcomb_T(t)=omega_0 textcomb_omega_0(omega)$$



      where
      $$textcomb_A(x)triangleqsum_n=-infty^+inftydelta(x-nA)$$






      share|cite|improve this answer






















      • Thanks, this is great. Do you recommend any books for this topic? Can you elaborate on how you compute the Fourier transform of $e^j n omega_0 t$?
        – littleO
        Aug 28 '16 at 0:17










      • The content can be found on most relevant books. However, if you look at signal processing textbooks you may find similar topics. The Fourier transform of $e^jnomega_0t$ can be found simply by recalling the "frequency shifting" property of Fourier transform, that is : $mathcalFe^jnomega_0tg(t)=G(omega-nomega_0)$ and the fact that $mathcalF1=2pidelta(omega)$.
        – msm
        Aug 28 '16 at 1:41






      • 1




        In order to get to $mathcalF1=2pidelta(omega)$ itself, one needs to accept $mathcalFdelta(t)=1$ and then use the "duality" property of Fourier transform that is : $mathcalFF(-t)=2pi f(omega)$. If you are interested in why $mathcalFdelta(t)=1$ as well, assume a form of pulse such as Gaussian, triangle, rectangle, etc. in the time domain and limit the pulse width to zero (i.e. $delta(t)$). You will get a frequency representation that expands more and more and tends to a constant in limit.
        – msm
        Aug 28 '16 at 2:57











      • Shouldn't the Fourier coefficients for $operatornamecomb_T (t)$ be $frac2T$, since we have $$frac1T int_0^T operatornamecomb_T (t) e^-jnomega_0 t operatornamedt = frac1T int_0^T big( delta(t) + delta(t-T) big) operatornamedt ?$$ This leads to an extra factor $2$ in your Fourier Transform of the comb function.
        – Mussé Redi
        Jun 2 at 15:22







      • 1




        I'm using the convention $$f(t) = frac12pi int_-infty^infty F(omega)e^iomega t operatornamedt .$$ Which convention are you using?
        – Mussé Redi
        Jun 2 at 15:28












      up vote
      9
      down vote



      accepted
      +50







      up vote
      9
      down vote



      accepted
      +50




      +50




      Assume an arbitrary periodic function $f(t)$ with period $T$. Consider the Fourier series representation of $f(t)$, in which $omega_0=frac2piT$:
      $$f(t)=sum_n=-infty^+inftyc_n e^i n omega_0 t$$
      Take the Fourier transform of the sides:
      beginalign
      mathcalFf(t)=&mathcalFsum_n=-infty^+inftyc_n e^i n omega_0 t\
      =&sum_n=-infty^+inftyc_nmathcalF e^i n omega_0 t\
      F(omega)=&2pisum_n=-infty^+inftyc_ndelta(omega-nomega_0)
      endalign
      This means that the Fourier transform of a periodic signal is an impulse train where the impulse amplitudes are $2pi$ times the Fourier coefficients of that signal.



      With $f(t)=delta(t)$, the Fourier series coefficients are $c_n=frac1T$ for all $n$.



      Hence,
      $$mathcalFsum_n=-infty^+inftydelta(t-nT)=frac2piT sum_n=-infty^+inftydelta(omega-nomega_0)$$
      or in comb notation:
      $$boxedmathcalFtextcomb_T(t)=omega_0 textcomb_omega_0(omega)$$



      where
      $$textcomb_A(x)triangleqsum_n=-infty^+inftydelta(x-nA)$$






      share|cite|improve this answer














      Assume an arbitrary periodic function $f(t)$ with period $T$. Consider the Fourier series representation of $f(t)$, in which $omega_0=frac2piT$:
      $$f(t)=sum_n=-infty^+inftyc_n e^i n omega_0 t$$
      Take the Fourier transform of the sides:
      beginalign
      mathcalFf(t)=&mathcalFsum_n=-infty^+inftyc_n e^i n omega_0 t\
      =&sum_n=-infty^+inftyc_nmathcalF e^i n omega_0 t\
      F(omega)=&2pisum_n=-infty^+inftyc_ndelta(omega-nomega_0)
      endalign
      This means that the Fourier transform of a periodic signal is an impulse train where the impulse amplitudes are $2pi$ times the Fourier coefficients of that signal.



      With $f(t)=delta(t)$, the Fourier series coefficients are $c_n=frac1T$ for all $n$.



      Hence,
      $$mathcalFsum_n=-infty^+inftydelta(t-nT)=frac2piT sum_n=-infty^+inftydelta(omega-nomega_0)$$
      or in comb notation:
      $$boxedmathcalFtextcomb_T(t)=omega_0 textcomb_omega_0(omega)$$



      where
      $$textcomb_A(x)triangleqsum_n=-infty^+inftydelta(x-nA)$$







      share|cite|improve this answer














      share|cite|improve this answer



      share|cite|improve this answer








      edited Aug 30 at 3:40

























      answered Aug 27 '16 at 11:16









      msm

      6,0492727




      6,0492727











      • Thanks, this is great. Do you recommend any books for this topic? Can you elaborate on how you compute the Fourier transform of $e^j n omega_0 t$?
        – littleO
        Aug 28 '16 at 0:17










      • The content can be found on most relevant books. However, if you look at signal processing textbooks you may find similar topics. The Fourier transform of $e^jnomega_0t$ can be found simply by recalling the "frequency shifting" property of Fourier transform, that is : $mathcalFe^jnomega_0tg(t)=G(omega-nomega_0)$ and the fact that $mathcalF1=2pidelta(omega)$.
        – msm
        Aug 28 '16 at 1:41






      • 1




        In order to get to $mathcalF1=2pidelta(omega)$ itself, one needs to accept $mathcalFdelta(t)=1$ and then use the "duality" property of Fourier transform that is : $mathcalFF(-t)=2pi f(omega)$. If you are interested in why $mathcalFdelta(t)=1$ as well, assume a form of pulse such as Gaussian, triangle, rectangle, etc. in the time domain and limit the pulse width to zero (i.e. $delta(t)$). You will get a frequency representation that expands more and more and tends to a constant in limit.
        – msm
        Aug 28 '16 at 2:57











      • Shouldn't the Fourier coefficients for $operatornamecomb_T (t)$ be $frac2T$, since we have $$frac1T int_0^T operatornamecomb_T (t) e^-jnomega_0 t operatornamedt = frac1T int_0^T big( delta(t) + delta(t-T) big) operatornamedt ?$$ This leads to an extra factor $2$ in your Fourier Transform of the comb function.
        – Mussé Redi
        Jun 2 at 15:22







      • 1




        I'm using the convention $$f(t) = frac12pi int_-infty^infty F(omega)e^iomega t operatornamedt .$$ Which convention are you using?
        – Mussé Redi
        Jun 2 at 15:28
















      • Thanks, this is great. Do you recommend any books for this topic? Can you elaborate on how you compute the Fourier transform of $e^j n omega_0 t$?
        – littleO
        Aug 28 '16 at 0:17










      • The content can be found on most relevant books. However, if you look at signal processing textbooks you may find similar topics. The Fourier transform of $e^jnomega_0t$ can be found simply by recalling the "frequency shifting" property of Fourier transform, that is : $mathcalFe^jnomega_0tg(t)=G(omega-nomega_0)$ and the fact that $mathcalF1=2pidelta(omega)$.
        – msm
        Aug 28 '16 at 1:41






      • 1




        In order to get to $mathcalF1=2pidelta(omega)$ itself, one needs to accept $mathcalFdelta(t)=1$ and then use the "duality" property of Fourier transform that is : $mathcalFF(-t)=2pi f(omega)$. If you are interested in why $mathcalFdelta(t)=1$ as well, assume a form of pulse such as Gaussian, triangle, rectangle, etc. in the time domain and limit the pulse width to zero (i.e. $delta(t)$). You will get a frequency representation that expands more and more and tends to a constant in limit.
        – msm
        Aug 28 '16 at 2:57











      • Shouldn't the Fourier coefficients for $operatornamecomb_T (t)$ be $frac2T$, since we have $$frac1T int_0^T operatornamecomb_T (t) e^-jnomega_0 t operatornamedt = frac1T int_0^T big( delta(t) + delta(t-T) big) operatornamedt ?$$ This leads to an extra factor $2$ in your Fourier Transform of the comb function.
        – Mussé Redi
        Jun 2 at 15:22







      • 1




        I'm using the convention $$f(t) = frac12pi int_-infty^infty F(omega)e^iomega t operatornamedt .$$ Which convention are you using?
        – Mussé Redi
        Jun 2 at 15:28















      Thanks, this is great. Do you recommend any books for this topic? Can you elaborate on how you compute the Fourier transform of $e^j n omega_0 t$?
      – littleO
      Aug 28 '16 at 0:17




      Thanks, this is great. Do you recommend any books for this topic? Can you elaborate on how you compute the Fourier transform of $e^j n omega_0 t$?
      – littleO
      Aug 28 '16 at 0:17












      The content can be found on most relevant books. However, if you look at signal processing textbooks you may find similar topics. The Fourier transform of $e^jnomega_0t$ can be found simply by recalling the "frequency shifting" property of Fourier transform, that is : $mathcalFe^jnomega_0tg(t)=G(omega-nomega_0)$ and the fact that $mathcalF1=2pidelta(omega)$.
      – msm
      Aug 28 '16 at 1:41




      The content can be found on most relevant books. However, if you look at signal processing textbooks you may find similar topics. The Fourier transform of $e^jnomega_0t$ can be found simply by recalling the "frequency shifting" property of Fourier transform, that is : $mathcalFe^jnomega_0tg(t)=G(omega-nomega_0)$ and the fact that $mathcalF1=2pidelta(omega)$.
      – msm
      Aug 28 '16 at 1:41




      1




      1




      In order to get to $mathcalF1=2pidelta(omega)$ itself, one needs to accept $mathcalFdelta(t)=1$ and then use the "duality" property of Fourier transform that is : $mathcalFF(-t)=2pi f(omega)$. If you are interested in why $mathcalFdelta(t)=1$ as well, assume a form of pulse such as Gaussian, triangle, rectangle, etc. in the time domain and limit the pulse width to zero (i.e. $delta(t)$). You will get a frequency representation that expands more and more and tends to a constant in limit.
      – msm
      Aug 28 '16 at 2:57





      In order to get to $mathcalF1=2pidelta(omega)$ itself, one needs to accept $mathcalFdelta(t)=1$ and then use the "duality" property of Fourier transform that is : $mathcalFF(-t)=2pi f(omega)$. If you are interested in why $mathcalFdelta(t)=1$ as well, assume a form of pulse such as Gaussian, triangle, rectangle, etc. in the time domain and limit the pulse width to zero (i.e. $delta(t)$). You will get a frequency representation that expands more and more and tends to a constant in limit.
      – msm
      Aug 28 '16 at 2:57













      Shouldn't the Fourier coefficients for $operatornamecomb_T (t)$ be $frac2T$, since we have $$frac1T int_0^T operatornamecomb_T (t) e^-jnomega_0 t operatornamedt = frac1T int_0^T big( delta(t) + delta(t-T) big) operatornamedt ?$$ This leads to an extra factor $2$ in your Fourier Transform of the comb function.
      – Mussé Redi
      Jun 2 at 15:22





      Shouldn't the Fourier coefficients for $operatornamecomb_T (t)$ be $frac2T$, since we have $$frac1T int_0^T operatornamecomb_T (t) e^-jnomega_0 t operatornamedt = frac1T int_0^T big( delta(t) + delta(t-T) big) operatornamedt ?$$ This leads to an extra factor $2$ in your Fourier Transform of the comb function.
      – Mussé Redi
      Jun 2 at 15:22





      1




      1




      I'm using the convention $$f(t) = frac12pi int_-infty^infty F(omega)e^iomega t operatornamedt .$$ Which convention are you using?
      – Mussé Redi
      Jun 2 at 15:28




      I'm using the convention $$f(t) = frac12pi int_-infty^infty F(omega)e^iomega t operatornamedt .$$ Which convention are you using?
      – Mussé Redi
      Jun 2 at 15:28










      up vote
      3
      down vote













      Intuitive Explanation



      The Comb is a sum of Time Shifted Dirac Delta.



      The Fourier Transform of a Dirac Delta is known to be a constant.



      The Fourier Transform of a Time Shifted Function is known to be Fourier Transform of the function multiplied by a complex exponential factor which is $ exp(-i 2 pi f T) $



      Just apply this points to the Comb Function considered as a sum of Time Shifted Dirac Delta with distance $ kT $ and you get a sum of Frequency Shifted exponential functions, each of which multiplied by a constant.



      Finally use Euler’s Formula to consider complex exponentials as a periodic sinusoidal function and observe that you have constructive interference only in frequencies which are integer multiple of $ frac1T $






      share|cite|improve this answer
























        up vote
        3
        down vote













        Intuitive Explanation



        The Comb is a sum of Time Shifted Dirac Delta.



        The Fourier Transform of a Dirac Delta is known to be a constant.



        The Fourier Transform of a Time Shifted Function is known to be Fourier Transform of the function multiplied by a complex exponential factor which is $ exp(-i 2 pi f T) $



        Just apply this points to the Comb Function considered as a sum of Time Shifted Dirac Delta with distance $ kT $ and you get a sum of Frequency Shifted exponential functions, each of which multiplied by a constant.



        Finally use Euler’s Formula to consider complex exponentials as a periodic sinusoidal function and observe that you have constructive interference only in frequencies which are integer multiple of $ frac1T $






        share|cite|improve this answer






















          up vote
          3
          down vote










          up vote
          3
          down vote









          Intuitive Explanation



          The Comb is a sum of Time Shifted Dirac Delta.



          The Fourier Transform of a Dirac Delta is known to be a constant.



          The Fourier Transform of a Time Shifted Function is known to be Fourier Transform of the function multiplied by a complex exponential factor which is $ exp(-i 2 pi f T) $



          Just apply this points to the Comb Function considered as a sum of Time Shifted Dirac Delta with distance $ kT $ and you get a sum of Frequency Shifted exponential functions, each of which multiplied by a constant.



          Finally use Euler’s Formula to consider complex exponentials as a periodic sinusoidal function and observe that you have constructive interference only in frequencies which are integer multiple of $ frac1T $






          share|cite|improve this answer












          Intuitive Explanation



          The Comb is a sum of Time Shifted Dirac Delta.



          The Fourier Transform of a Dirac Delta is known to be a constant.



          The Fourier Transform of a Time Shifted Function is known to be Fourier Transform of the function multiplied by a complex exponential factor which is $ exp(-i 2 pi f T) $



          Just apply this points to the Comb Function considered as a sum of Time Shifted Dirac Delta with distance $ kT $ and you get a sum of Frequency Shifted exponential functions, each of which multiplied by a constant.



          Finally use Euler’s Formula to consider complex exponentials as a periodic sinusoidal function and observe that you have constructive interference only in frequencies which are integer multiple of $ frac1T $







          share|cite|improve this answer












          share|cite|improve this answer



          share|cite|improve this answer










          answered Aug 27 '16 at 12:15









          Nicola Bernini

          1361




          1361




















              up vote
              0
              down vote













              Up to constants and normalizations, this Dirac comb is its own Fourier transform: the assertion of this evaluated on (for example) a Schwartz function, $sum_nin mathbb Z f(n) ;=; sum_ninmathbb Z widehatf(n)$, is the Poisson summation formula.






              share|cite|improve this answer
























                up vote
                0
                down vote













                Up to constants and normalizations, this Dirac comb is its own Fourier transform: the assertion of this evaluated on (for example) a Schwartz function, $sum_nin mathbb Z f(n) ;=; sum_ninmathbb Z widehatf(n)$, is the Poisson summation formula.






                share|cite|improve this answer






















                  up vote
                  0
                  down vote










                  up vote
                  0
                  down vote









                  Up to constants and normalizations, this Dirac comb is its own Fourier transform: the assertion of this evaluated on (for example) a Schwartz function, $sum_nin mathbb Z f(n) ;=; sum_ninmathbb Z widehatf(n)$, is the Poisson summation formula.






                  share|cite|improve this answer












                  Up to constants and normalizations, this Dirac comb is its own Fourier transform: the assertion of this evaluated on (for example) a Schwartz function, $sum_nin mathbb Z f(n) ;=; sum_ninmathbb Z widehatf(n)$, is the Poisson summation formula.







                  share|cite|improve this answer












                  share|cite|improve this answer



                  share|cite|improve this answer










                  answered Jul 21 at 19:27









                  paul garrett

                  30.9k360116




                  30.9k360116



























                       

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