Simplifying equations involving Dirac Delta (Analog Signal Processing)

In summary, the conversation discusses the process of mixing two signals, finding the frequency response, and determining the output. The individual is having difficulty taking the Fourier transform and convolving two functions with different coefficients. They ask for advice on simplifying the problem and mention the possibility of breaking one function into smaller parts. A hint is given to use the fact that δ(-x) = δ(x) in the convolution expression.
  • #1
nameless912
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0

Homework Statement



Signal f(t) = (5+rect(t/4))cos(60pi*t) is mixed with signal cos(60pi*t) to produce signal y(t). Subsequently, y(t) is low-pass filtered with a system having frequency response H(w) = 4rect(w/(4*pi)) to produce q(t). Sketch F(ω), Y(ω), and Q(ω) and determine q(t).

I'm specifically having trouble with taking the Fourier transform of f(t) in order to sketch F(w) and also to move on with the rest of the problem.

Homework Equations



f(t) = (5+rect(t/4))cos(60pi*t)
mixed_signal = cos(60pi*t)

The Attempt at a Solution



I attempted to take the Fourier series as follows:
f(t) = (5+rect(t/4))cos(60pi*t)
= 5cos(60pi*t) + rect(t/4)cos(60pi*t)
I used the transformation for cos(w0t) and rect(t/4) to come up with
F(w) = 5pi(delta(w-60pi) + delta(w+60pi)) + sinc(2w) * pi(delta(w-60pi) + delta(w+60pi))
(note that asterisk in the last line indicates convolution not multiplication)

But now I can't figure out how to convolve sinc(2w) and delta(w-60pi) since they have different coefficients in front of w. I know that f(t) * delta(t-t0) = f(t-t0), but that formula doesn't seem to apply here...

I thought that maybe in order to simplify it I could break sinc(2w) into sin(w)cos(w)/w but that seems like it'll leave me with an insanely complex solution to try to do the inverse Fourier transform on later in the problem. Does anyone have any ideas?
 
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  • #2
What is the problem convolving sinc(2w) and δ(w - w0)?

Write out the convolution integral for these two functions of w. (Pick the appropriate one; there are two versions).

Then, big hint: δ(-x) = δ(x) and you have your convolution expression in w.
 

1. What is the Dirac Delta function?

The Dirac Delta function, denoted by δ(t), is a mathematical function used in analog signal processing to represent an impulse or spike in a signal. It is defined as having an infinite amplitude at t=0 and a width of 0, while being 0 everywhere else.

2. Why is the Dirac Delta function useful in simplifying equations?

The Dirac Delta function is useful in simplifying equations because it allows us to represent a complex signal as a sum of simpler signals. This makes it easier to solve equations and analyze signals in analog signal processing.

3. How is the Dirac Delta function used in convolution?

In convolution, the Dirac Delta function is used as the impulse response of a system. This means that when convolving a signal with the Dirac Delta function, we are essentially passing the signal through the system and observing its output. This is a useful tool in analyzing the behavior of systems in analog signal processing.

4. Can the Dirac Delta function be integrated or differentiated?

Yes, the Dirac Delta function can be integrated and differentiated. However, its integration and differentiation follow certain rules and properties that are specific to the Dirac Delta function, such as the sifting property and the scaling property.

5. Are there any limitations to using the Dirac Delta function in simplifying equations?

Yes, there are limitations to using the Dirac Delta function in simplifying equations. The Dirac Delta function is only defined for real values of t and cannot be used in complex analysis. Additionally, it is an idealized function and does not exist in the physical world, so it should be used with caution and only in mathematical representations of signals and systems.

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