Find a piecewise smoother parameterization of C

  • Thread starter whynot314
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In summary, the conversation discusses the process of building a parametrization of a path and understanding how the book arrived at the answer. The conversation includes a suggested formula and explanation for each leg of the path, as well as a suggestion to test the formula to ensure it is correct.
  • #1
whynot314
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I am having a real tough time trying to build a parametrization of the path c. its a really simple one but my professor just briefly went over it, and I can't find the thought process to put it together. I know the equation of a plane curve r(t)=x(t)i+y(t)j and everything. But its just not making sense to me. I would really like to understand how the book got this answer, I know there are many answers but if I can figure this one out i might be able to see other ways. If you know a good vid for this stuff please link it.[PLAIN]http://i1341.photobucket.com/albums/o745/nebula-314/IMAG0094.jpg[/PLAIN]
 
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  • #2
Well,

c1: (x,y) = (t,0) : 0 < t ≤ 3
c2: (x,y) = (3,t-3) : 3 < t ≤ 6
c3: ... you should be able to figure the rest.

Then you can integrate from t=0 to t=12.

This is pretty much what the book says - but they use unit vectors.
To understand it, put a dot on the graph at the t=0 position, then watch where it goes as t gets bigger.
 
  • #3
whynot314 said:
I am having a real tough time trying to build a parametrization of the path c. its a really simple one but my professor just briefly went over it, and I can't find the thought process to put it together. I know the equation of a plane curve r(t)=x(t)i+y(t)j and everything. But its just not making sense to me. I would really like to understand how the book got this answer, I know there are many answers but if I can figure this one out i might be able to see other ways. If you know a good vid for this stuff please link it.
IMAG0094.jpg

Since you already have the answer in the book, maybe it would make more sense to see why their parameterization works.

For the first leg, r(t) = ti, 0 ≤ t ≤ 3
Each value of t will get you to a point on the x-axis between 0 and 3. When t = 3, you're at the point (3, 0).

For the second leg, all the x values are 3, which explains the 3i component.
For the vertical component we want to map the t values from 3 to 6 to the values 0 to 3, so we subtract 3. This gives us r(t) = 3i + (t - 3)j, 3 ≤ t ≤ 6.
When t = 3, we're at the point (3, 0). When t = 4.5, we're at the point (3, 1.5). When t = 6, we're at (3, 3).

For the third leg, the y-value stays fixed at 3, but the x-value has to go from 3 down to 0, while the t values range from 6 to 9. If we were mapping [6, 9] to [0, 3] we could use t - 6, but we want to end up with [3, 0], so t - 6 won't work. Switching the order from t - 6 to 6 - t maps the t values in [6, 9] to x values of 0 to -3, so they're off. If we adjust by adding 3 to 6 - t, we get 9 - t, and this correctly maps t values between 6 and 9 to x values from 3 down to 0. So r(t) = (12 - t)i + 0j, 6 ≤ t ≤ 9.

The last leg keeps x fixed at 0, but maps t values from 9 to 12 onto y values from 3 down to 0. I leave it for you to figure out a formula for this part.
 
  • #4
ok I think I kind of got it now, I tried this one. And found a piecewise, does this one work?
[PLAIN]http://i1341.photobucket.com/albums/o745/nebula-314/IMAG0095.jpg[/PLAIN]
 
  • #5
Test it and see. You have c1(t) = 1 - t for 0 <= t <= 2. You need to include i in your formula.

Does c1(0) give you the point (1, 0)?
Does c1(2) give you the point (-1, 0)?

Same thing for the other two legs.
 
  • #6
I think you made a mistake on the second one. C1 ends at -i but C2 starts you at -i + j
 
  • #7
k found my mistake on C2 and believe it to be (t-2)j

so I now have c1 r(t)=(1-t)i 0≤t≤2
C2 r(t)=(t-3)i +(t-2)j 2≤t≤3
c3 r(t)=(t-3)i +(4-t)j 3≤t≤4

I think this is correct.
 

1. What is a piecewise smoother parameterization?

A piecewise smoother parameterization is a mathematical technique used to represent a continuous curve or function by breaking it into smaller segments, each of which is represented by a simpler, smoother function. This allows for a more accurate and efficient representation of the original curve.

2. How is a piecewise smoother parameterization different from other parameterization methods?

A piecewise smoother parameterization differs from other methods in that it breaks the curve into segments and uses simpler functions to represent each segment, rather than using a single complex function to represent the entire curve. This results in a more accurate representation with fewer parameters.

3. What is the purpose of finding a piecewise smoother parameterization?

The purpose of finding a piecewise smoother parameterization is to simplify the representation of a curve or function, making it easier to analyze and manipulate. This can be particularly useful in data analysis and modeling, where a simpler representation can lead to more accurate and efficient results.

4. How is a piecewise smoother parameterization determined?

A piecewise smoother parameterization is typically determined using algorithms and mathematical techniques that identify the optimal breakpoints and simpler functions to use for each segment. This process involves minimizing an error function that measures the difference between the original curve and the piecewise representation.

5. What are the benefits of using a piecewise smoother parameterization?

Using a piecewise smoother parameterization can result in a more accurate and efficient representation of a curve, particularly when the original curve is complex or contains sharp changes. It can also make the curve easier to interpret and manipulate, allowing for better analysis and modeling.

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