Simpson method question(numerical analysis)

In summary: In Simpson's rule, you divide an interval [a, b] into n subintervals of equal length. In each subinterval you use function values evaluated at three points: the left endpoint, the middle, and the right endpoint. x_0=ax_1=0x_2=b-ax_3=0x_4=1
  • #1
nhrock3
415
0
i have been told that simpson with 3 points is a single panel

??

why??

a pannel is the distance between to points
so if we have 3 points then we have 2 panels
??

http://i48.tinypic.com/nlc4t1.jpg
 
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  • #2
can't view the link clearly and what do you mean by pannel?
 
  • #3
Simpson's method works by approximating a function by a "piecewise quadratic". If I understand your use of "panel" correctly, it is one of the quadratic pieces.

Since a quadratic, [itex]y= ax^2+ bx+ c[/itex], has three coefficients to be determined, one quadratic, one panel, requires three points, not two, to determine those three coefficients.

The "trapezoid method", where we approximate the function by a piecewise linear function, y= ax+ b, requires only two coefficients to be determined and so each "panel" requires two points.
 
  • #4
so how they use those three points in the formula
i can't see where they use them on the arrow pointed formula
 
  • #5
In the last equation, the three points are (-1, f(-1)), (0, f(0)), and (1, f(1)).

The equation could be rewritten as
S1 = (1/3)[f(-1) + 4f(0) + f(1)].
 
  • #6
so a pannel is not an interval
a panel in simpsons rule is 3 points (which has two intervals between them)
 
  • #7
thanks :)
 
  • #8
Mark44 said:
In the last equation, the three points are (-1, f(-1)), (0, f(0)), and (1, f(1)).

The equation could be rewritten as
S1 = (1/3)[f(-1) + 4f(0) + f(1)].

i tried to get to your expression by the formula
if we have three points then we have 2 sub intervals
[tex]h=\frac{b-a}{m}=2/2=1[/tex]
[tex]x_h=a+kh=-1+k[/tex]
[tex]s(f,h)=\frac{h}{3}(f(a)+f(b)+\frac{2h}{3}\sum_{k=1}^{m}f(x_{2k})+\frac{4h}{3}\sum_{k=1}^{m}f(x_{2k-1})=[/tex]
[tex]\frac{1}{3}(f(-1)+f(1)+\frac{2}{3}\sum_{k=1}^{m}f(x_{2k})+\frac{4}{3}\sum_{k=1}^{m}f(x_{2k-1})=[/tex]

[tex]\frac{1}{3}(f(-1)+f(1)+\frac{2}{3}[f(x_2)+f(x_4)]+\frac{4}{3}[f(x_1)+f(x_3)]=
[/tex]
you see that it requests 4 points
and not
x_0 x_1 x_2

??
 
Last edited:
  • #9
In Simpson's rule, you divide an interval [a, b] into n subintervals of equal length. In each subinterval you use function values evaluated at three points: the left endpoint, the middle, and the right endpoint.

Instead of getting lost in the summation symbols, work out for yourself for some simple function and an interval [0, 1] divided into four subintervals. What does Simpson's rule give you for this situation?
 

1. What is the Simpson method in numerical analysis?

The Simpson method, also known as Simpson's rule, is a numerical integration technique used to approximate the area under a curve. It divides the area into multiple smaller segments and uses a quadratic polynomial to approximate the curve within each segment.

2. How does the Simpson method work?

The Simpson method works by dividing the area under a curve into smaller segments and approximating each segment with a quadratic polynomial. The area under each segment is then calculated by finding the area under the polynomial using integration. The total area is then calculated by summing up the areas of all the segments.

3. What is the formula for the Simpson method?

The formula for the Simpson method is: A = (h/3)(f(x0) + 4f(x1) + 2f(x2) + 4f(x3) + ... + 4f(xn-1) + f(xn)), where h is the width of each segment and f(x) is the function being integrated.

4. When should the Simpson method be used?

The Simpson method should be used when the function being integrated is smooth and continuous, and when a more accurate approximation of the area under the curve is needed compared to other numerical integration methods such as the trapezoidal rule.

5. What are the advantages of using the Simpson method?

The advantages of using the Simpson method include its high accuracy when used on smooth and continuous functions, its ability to handle both concave and convex curves, and its simplicity in implementation compared to other numerical integration methods.

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