Fourier Transform- is this right?

In summary, the solution for computing the Fourier transform of x(t) is to use the definition of the Fourier transform, the properties of the delta function, and the sinc function. The solution provided is correct, but could be made clearer by using common notation and including more explanations or steps.
  • #1
FrogPad
810
0
If someone wouldn't mind checking if this answer is correct, that would be awesome.

[tex] x(t) = [/tex] a triangle with points (-2,0), (0,1), and (2,0).

I am supposed to compute the Fourier transform ([itex] \hat x (\omega) [/itex]) of [itex] x(t) [/itex].

"Solution"
[tex] m = \frac{y_2-y_1}{x_2-x_1}=\frac{1}{2} [/tex]

Thus, [tex] \frac{dx(t)}{dt} = [/tex] a pulse with height [itex] \frac{1}{2} [/tex] from (-2 to 0), and a pulse with height [itex] \frac{-1}{2} [/itex] from (0 to 2).

Let [tex] k(t) = \frac{dx(t)}{dt} [/tex]

Since, [tex]x(t) = \int_{-\infty}^x k(t)dt \leftrightarrow \frac{1}{j\omega} \hat k(\omega) + \hat k(0) \delta(\omega) [/tex]

Let [tex] x'(t) = [/tex] a pulse from -1 to 1 with height 1

Then, [tex] \frac{1}{2} x'(t) \leftrightarrow \frac{\sin \omega}{\omega} [/tex]

and, [tex] k(t) = \frac{1}{2}x'(t+1) - \frac{1}{2}x'(t-1) [/tex]

Thus, [tex] \hat k(\omega) = e^{j\omega}\frac{\sin \omega}{\omega} - e^{-j\omega}\frac{\sin \omega}{\omega} [/tex]

[tex] \hat x (\omega) = \frac{2 \sin_c \omega}{\omega} \left( \frac{e^{j\omega}-e^{-j\omega}}{2j} \left) + 2 \sin_c(0)\cos(0)\delta(\omega) = 2 ( \sin_c^2 \omega + \delta(\omega)) [/tex]note: [tex] \sin_c(x) = \frac{sin x}{x} [/tex] (I don't know how to write the sinc function)
Does this look right?

Thanks
 
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  • #2
for your post! Your solution looks correct to me. However, I would suggest using the notation \mathrm{sinc}(x) = \frac{\sin x}{x} for the sinc function. It is a common notation and will make your solution clearer for others to read. Additionally, you may want to include some explanations or steps in your solution to make it easier for others to follow. Overall, great job!
 

FAQ: Fourier Transform- is this right?

What is a Fourier Transform?

A Fourier Transform is a mathematical tool used to decompose a signal into its frequency components. It converts a signal from its original form in the time domain to a representation in the frequency domain.

Why is the Fourier Transform important?

The Fourier Transform is important because it allows us to analyze signals in terms of their frequency components, which can provide valuable insights and information about the signal. It has numerous applications in fields such as signal processing, image processing, and data analysis.

What is the difference between a Fourier Transform and a Fourier Series?

A Fourier Transform is used for continuous signals, while a Fourier Series is used for periodic signals. A Fourier Transform converts a signal into its frequency components, while a Fourier Series decomposes a periodic signal into a sum of sine and cosine waves.

How is the Fourier Transform calculated?

The Fourier Transform is calculated using an integral formula, which involves taking the complex exponential of the signal and integrating it over all frequencies. However, this integral formula can be computationally intensive, so there are also more efficient algorithms, such as the Fast Fourier Transform, that can be used to calculate it.

What is the inverse Fourier Transform?

The inverse Fourier Transform is the mathematical operation that converts a signal from its frequency domain representation back to its original form in the time domain. It is essentially the reverse process of the Fourier Transform.

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