Graphing Fourier Spectra of AM Signals with Sin^3 Carrier

In summary, the conversation discusses graphing the signal spectra of an AM signal where the message m(t) is multiplied by a sine function instead of a cosine function. The person is also struggling with finding the Fourier transform of sin(3x). The equations used to find the Fourier transform are Euler's identity for sine and the output function for the signal. However, without knowing the specific function for m(t), it is difficult to complete the graph or find the second portion of the answer.
  • #1
scubaman
5
0

Homework Statement



I am trying to figure out how to graph the signal spectra of an AM signal where the message m(t) is multiplied by the carrier, which is sin^3 (wt) instead of cos (wt). I can do the FT but I do not know how to graph this since there are imaginary numbers as coefficients

Also, I do not know how to do the Fourier transform of say sin(3x). You get to this point:

kj/8 ∫m(t) e^-j6pi(f-f0)t dt what do I do with the 6pi?

Homework Equations



Euler's identity for sin(x), sin^3(x) = (3/4)sin(x) - (1/4)sin(3x)

y(t), the output, = km(t)sin^3(ωt)

The Attempt at a Solution



Using these two equations I have found the FT of the signal to be as follows:

Y(f) = -[((3kj)/8)F(f-f0) + ((3kj)/8)F(f+f0)] + F{ the sin(3x) function, which IDK how to do!}

Just don't know how to graph that or get the second portion of the answer. Thanks
 
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  • #2
I don't see how you can graph anything if you're not given what m(t) is. Such as m(t) = m0 sin(w0t)?
 

1. What is a Fourier spectrum problem?

A Fourier spectrum problem is a mathematical problem that involves analyzing the frequencies present in a signal or function. It involves breaking down a complex signal into its component frequencies, known as the Fourier spectrum, using the Fourier transform.

2. Why is the Fourier spectrum important?

The Fourier spectrum is important because it allows us to understand the frequency components present in a signal. This can provide valuable information about the signal and its characteristics, such as the dominant frequencies or the presence of noise.

3. How is the Fourier spectrum calculated?

The Fourier spectrum is calculated using the Fourier transform, which is a mathematical operation that decomposes a function into its constituent frequencies. There are different methods for calculating the Fourier transform, such as the discrete Fourier transform (DFT) or the fast Fourier transform (FFT).

4. What are some real-life applications of Fourier spectrum analysis?

Fourier spectrum analysis has many practical applications in fields such as engineering, physics, and signal processing. It is commonly used in image and audio processing, data compression, and in the analysis of vibrations and other physical phenomena.

5. Are there any limitations to Fourier spectrum analysis?

One limitation of Fourier spectrum analysis is that it assumes the signal is periodic, which may not always be the case in real-world applications. Additionally, it may not be able to accurately capture high-frequency components or subtle changes in the signal. Other methods, such as wavelet analysis, may be better suited for these scenarios.

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