Fourier series representation of delta train

In summary, the Fourier series of a delta train, which is represented by a Dirac comb or impulse train, is equal to (1/T) + (2/T)Ʃcos(nωt) where T is the period and ω=2*Pi/T. This series does not converge to the delta function we want, but it converges to a generalized function given by f(t) = (1-(t/T)) + Ʃu(t-nT), where u is the Heaviside function. The derivative of this function is equal to the Fourier series for the impulse train, but the plot may not match exactly due to limitations of computer calculations.
  • #1
Aziza
190
1
The Fourier series of a delta train is supposedly (1/T) + (2/T ) Ʃcos(nωt) ...
where T is period and ω=2*Pi/T ...but when I plot this, it doesn't give me just a spike towards positive infinity, but towards negative infinity as well (see attached pic), so this does not seem to converge to the delta function we want... ?

Also I am kindof confused as to how this is actually derived. The way my book does it is it starts with a backwards sawtooth wave. The derivative of this is a delta train, with the deltas going towards positive infinity...the Fourier series of this sawtooth wave is
f(t) = (1/2) + (2/T ) Ʃ(1/n)sin(nωt)
But f(t) can also be written as a generalized function:
f(t) = (1-(t/T)) + Ʃu(t-nT)
where u is the heavyside function

Taking derivative of first f(t) gives
f'(t) = (2/T ) Ʃcos(nωt) (1)

But taking derivative of second f(t) gives
f'(t) = -(1/T) + Ʃδ(t-nT) (2)

Ok I understand everything so far, but now my book says that equation (1) doesn't converge 'in the ordinary sense' but 'we can say that this series converges to the generalized function' given by equation (2)...huh? How can (1) converge to (2) if (1) gives a different graph than (2) ?? That is my first confusion.

Next the book just equates (1) and (2) and so gets the Fourier series for Ʃδ(t-nT)...but I am confused as to why we can just equate them if they are not really the same thing...
 

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  • #2
Aziza said:
The Fourier series of a delta train is supposedly (1/T) + (2/T ) Ʃcos(nωt) ...
where T is period and ω=2*Pi/T ...but when I plot this, it doesn't give me just a spike towards positive infinity, but towards negative infinity as well (see attached pic), so this does not seem to converge to the delta function we want... ?

Also I am kindof confused as to how this is actually derived. The way my book does it is it starts with a backwards sawtooth wave. The derivative of this is a delta train, with the deltas going towards positive infinity...the Fourier series of this sawtooth wave is
f(t) = (1/2) + (2/T ) Ʃ(1/n)sin(nωt)
But f(t) can also be written as a generalized function:
f(t) = (1-(t/T)) + Ʃu(t-nT)
where u is the heavyside function

Taking derivative of first f(t) gives
f'(t) = (2/T ) Ʃcos(nωt) (1)

But taking derivative of second f(t) gives
f'(t) = -(1/T) + Ʃδ(t-nT) (2)

Ok I understand everything so far, but now my book says that equation (1) doesn't converge 'in the ordinary sense' but 'we can say that this series converges to the generalized function' given by equation (2)...huh? How can (1) converge to (2) if (1) gives a different graph than (2) ?? That is my first confusion.

Next the book just equates (1) and (2) and so gets the Fourier series for Ʃδ(t-nT)...but I am confused as to why we can just equate them if they are not really the same thing...

I think you may be trying to describe a Dirac comb ("impulse train").

You probably made the plot using a computer, right? Computers are not made to calculate infinite sums. Thus, your plot is an approximation of the Fourier series.

Go with the math. If two functions are equal, then their derivatives are probably equal.
 

1. What is a Fourier series representation of a delta train?

A Fourier series representation of a delta train is a mathematical tool used to represent a periodic signal as a sum of sinusoidal functions. It is especially useful for analyzing signals that contain sharp, sudden changes or impulses, such as a delta train.

2. How is a Fourier series representation of a delta train calculated?

A Fourier series representation of a delta train is calculated by finding the coefficients of the various sinusoidal functions that, when added together, accurately represent the periodic signal. This is done using the Fourier series formula, which involves integrating the signal over one period.

3. What is the significance of a Fourier series representation of a delta train?

A Fourier series representation of a delta train is significant because it allows us to analyze and manipulate signals that contain impulses or sharp changes. This is important in many fields, such as engineering, physics, and signal processing.

4. What are the applications of a Fourier series representation of a delta train?

A Fourier series representation of a delta train has various applications, including signal analysis, data compression, and signal filtering. It is also used in fields such as image processing, audio processing, and communication systems.

5. Are there any limitations to using a Fourier series representation of a delta train?

Yes, there are some limitations to using a Fourier series representation of a delta train. It is only applicable to signals that are periodic and can be represented as a sum of sinusoidal functions. It also assumes that the signal has a finite energy and does not account for any noise or distortion in the signal.

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