Signals and Systems: Determine the convolution of x(t) and h(t)

  • #1
SumDood_
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Homework Statement
Determine the convolution of x(t) and h(t)
Relevant Equations
Specified in the solution attempt
So, the convolution of two signals is described as follows:
$$ \int_{-\infty}^{\infty} x(\tau)h(t-\tau) \, d\tau $$
The figure shows the given signals. Now, as described in the convolution integral, I transformed ##h(t)## to ##h(-\tau)## by flipping the signal horizontally. So, now I have an impulse signal when ##\tau = -2##.

Now, the ##t## represents a horizontal shift in signal ##h(t-\tau)##. After which both signals are multiplied and then integrated. When, ##t<1##, then there is no overlap between ##h(\tau)## and ##x(\tau)##. The same is true when ##t>5##.
Now, I need to determine what the limits of the integration would be when there is an overlap between the two signals. If ##h(\tau)## were a rectangular signal, then it would be straightforward.
1691869231971.png


The impulse signal means the only overlap between the two signals exist at the exact point to where the impulse is shifted. Because of this, I don't know how to find the limits to evaluate the convolution integration. From what I have read online, I see that the output signal ##y(t)## is probably a horizontal shifted signal of ##x(t)## by 2 units to the right.

I can't seem to get the answer because I don't know what the limits of the integration are supposed to be. I thought the upper limit and the lower limit would be equal, but then the integration would evaluate to 0.
 
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  • #3
The limits are always from ##-\infty## to ##\infty##. It is not not very important for this example because ##h(t)## is only nonzero at one point. You do not need to consider the limits to evaluate the integral. You should look at where that point is involved in the convolution integral. That convolution is a function of ##t##.
 
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  • #5
FactChecker said:
The limits are always from ##-\infty## to ##\infty##. It is not not very important for this example because ##h(t)## is only nonzero at one point. You do not need to consider the limits to evaluate the integral. You should look at where that point is involved in the convolution integral. That convolution is a function of ##t##.
Makes sense now.
Thanks!
 
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Related to Signals and Systems: Determine the convolution of x(t) and h(t)

What is convolution in the context of signals and systems?

Convolution is a mathematical operation used to determine the output of a linear time-invariant (LTI) system when an input signal is applied. It combines two signals, typically an input signal x(t) and an impulse response h(t), to produce a third signal y(t), representing the system's output.

How do you mathematically define the convolution of two continuous-time signals?

The convolution of two continuous-time signals x(t) and h(t) is defined by the integral:\[ y(t) = (x * h)(t) = \int_{-\infty}^{\infty} x(\tau) h(t - \tau) \, d\tau \]This integral computes the area under the product of x(τ) and a time-reversed and shifted version of h(t).

What steps are involved in calculating the convolution of two signals?

The steps to calculate the convolution of two signals x(t) and h(t) are:1. Flip one of the signals, typically h(t), to get h(-τ).2. Shift the flipped signal by t to get h(t - τ).3. Multiply the shifted signal by the other signal x(τ).4. Integrate the product over all τ to get the output y(t) for each value of t.

Can you provide an example of convolution for two simple signals?

Sure, consider x(t) as a rectangular pulse of width 1 centered at t=0, and h(t) as another rectangular pulse of width 1 centered at t=0. The convolution y(t) will be a triangular pulse of width 2 centered at t=0. Mathematically, if x(t) = rect(t) and h(t) = rect(t), then:\[ y(t) = \int_{-\infty}^{\infty} \text{rect}(\tau) \text{rect}(t - \tau) \, d\tau \]The result is a triangular function with a peak at t=0 and width 2.

What are some common applications of convolution in signals and systems?

Convolution is widely used in various applications, including:1. Signal processing: Filtering signals to remove noise or extract features.2. Communications: Modulating and demodulating signals.3. Control systems: Analyzing system response to inputs.4. Image processing: Blurring, sharpening, and edge detection in images.5. Audio processing: Reverb and echo effects in sound engineering.

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