Fourier Transform Rect function

In summary, you correctly used the formula for the Fourier transform, but you need to integrate over the correct interval and use the correct function for v(t). You also need to use the appropriate Fourier transform properties for the cosine and sine functions to simplify the integral. With these corrections, your answer is correct.
  • #1
yoamocuy
41
0

Homework Statement


Find the Fourier transform of A∏((t-T)/(2*T)).


Homework Equations


V(F)=∫v(t)*e-j*2*pi*f*t


The Attempt at a Solution


∫(A*e-j*2*pi*f*t,t,0,2T)
= A*sin(4*f*pi*T)/(2*f*pi*T)+j(A*cos(4*pi*f*T)-A)/(2*pi*f)
=2*A*T*sinc(4*f*T)+j*(A*cos(4*pi*f*T)-A)/(2*pi*f)

The answer's supposed to be = 2*A*T*sinc(2*f*T)*e-j*2*pi*f*T

Is everything I've done so far ok? How do I go about simplifying the cos into an e log?
 
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  • #2


Your attempt at a solution is on the right track, but there are a few errors in your calculations. Let's go through it step by step.

First, you have the correct formula for the Fourier transform, but you need to use the function A∏((t-T)/(2*T)) as your v(t). This means that you need to integrate from -∞ to ∞, not from 0 to 2T. So your integral should be:

∫(A∏((t-T)/(2*T))*e-j*2*pi*f*t,t,-∞,∞)

Next, when you integrate e-j*2*pi*f*t, you should use the fact that e-j*2*pi*f*t = cos(2*pi*f*t) - j*sin(2*pi*f*t). So your integral becomes:

∫(A∏((t-T)/(2*T))*(cos(2*pi*f*t) - j*sin(2*pi*f*t)),t,-∞,∞)

Now, we can break this integral into two parts and focus on just one at a time. Let's start with the first part, where we have the cosine function:

∫(A∏((t-T)/(2*T))*cos(2*pi*f*t),t,-∞,∞)

To solve this integral, we can use the fact that the Fourier transform of a cosine function is a delta function. This means that the integral will be equal to A*(2*T)*δ(f-1/2T). So our first part becomes:

A*(2*T)*δ(f-1/2T)

Now, for the second part where we have the sine function, we can use the fact that the Fourier transform of a sine function is j*sign(f)*A*sinc(2*f*T). So our second part becomes:

j*sign(f)*A*sinc(2*f*T)

Putting these two parts together, we get the final answer:

A*(2*T)*δ(f-1/2T) + j*sign(f)*A*sinc(2*f*T)

This is equivalent to the answer given in the forum post: 2*A*T*sinc(2*f*T)*e-j*2*pi*f*T. So your final answer is correct, but you just need to show the steps and calculations to get there.
 

FAQ: Fourier Transform Rect function

What is a Fourier Transform Rect function?

A Fourier Transform Rect function, also known as a rectangular function, is a mathematical function that represents a rectangle in the time or space domain. It has a value of 1 within a certain interval and 0 everywhere else. It is often used in signal processing and image analysis.

How is a Fourier Transform Rect function calculated?

A Fourier Transform Rect function is calculated by taking the inverse Fourier transform of the sinc function, which is the Fourier transform of a rectangular function. This can be done using mathematical equations or with the help of software programs such as MATLAB.

What are the properties of a Fourier Transform Rect function?

A Fourier Transform Rect function has several important properties, including being an even function, having a constant value of 1 within a specific interval, and having a value of 0 outside of that interval. It also has a Fourier transform that is a sinc function, and its inverse Fourier transform is a sinc function as well.

What is the significance of a Fourier Transform Rect function in signal processing?

A Fourier Transform Rect function is commonly used in signal processing as it can be used to filter out unwanted frequencies in a signal. Its rectangular shape allows for a sharp cutoff of frequencies, making it useful for removing noise or unwanted components from a signal.

Are there any real-world applications of Fourier Transform Rect functions?

Yes, there are several real-world applications of Fourier Transform Rect functions. They are commonly used in digital signal processing, image processing, and audio processing. They are also used in the design of filters, such as low-pass, high-pass, and band-pass filters, and in the analysis of periodic signals and systems.

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