Solving f(x)=e^(0.1x^2) with H5, H3 and Error Bounds

In summary: Therefore, the approximations are equal, but we need to find the error bounds to determine which approximation is more accurate. To find the error bounds, use the formula:|f(x) - P_n(x)| <= M_n(x) * (x-x_0)(x-x_1)...(x-x_n)where f(x) is the original function, P_n(x) is the Lagrange polynomial of degree n, and M_n(x) is the maximum value of the n+1 derivative of f(x) on the interval [x0, xn].For H5 (1.25):|f(1.25
  • #1
stunner5000pt
1,461
2
The data \below gives the list of values for [itex] f(x) = e^{0.1x^2} [/itex]
Approximate f(1.25) by using H5 (1.25) and H3 (1.25) wqhere H5 uses nodes x0 =1, x1 =2, x2 = 3. and H3 uses nodes x0=1, x1 = 1.5
Find error bounds for those approximations

this questio nand its data table is given in question on this link
http://people.math.yorku.ca/poliakov/3241f05/3241a4.pdf

So first i have to find the lagrange polynomials
But hwat does it mean [itex] L_{2,0} (x) [/itex] or [itex] L_{2,1) (x) [/itex]
im sorry I am asking such an elementary question because my textbook is not specific at all and all web searches yield info that is not useful to solving this

Please help me on this. Also can you have a look at number 4. How would i do tha. Similarly ik now i have to find Sj. But how iw Sj defined? So suppose i were to find S0 then Xj in this case is 0? How do you find aj bj and so on however? Please help! I really need to able to solve this...

Thank you for your help!
 
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  • #2
The Lagrange polynomials L_{2,0} (x) and L_{2,1} (x) are polynomials of degree 2 that pass through the points (x0, f(x0)), (x1, f(x1)), and (x2, f(x2)). In this case, the nodes x0, x1, and x2 are 1, 1.5, and 2, respectively. To find the Lagrange polynomials, you need to solve a system of linear equations. First, solve for the coefficients of the polynomial:L_{2,0}(x) = a_0 + a_1x + a_2x^2Then, substitute the three given points into the equation and solve the resulting system of equations for the coefficients a0, a1, and a2.For example, for L_{2,0} (x):a_0 + a_1(1) + a_2(1)^2 = e^{0.1(1)^2}a_0 + a_1(1.5) + a_2(1.5)^2 = e^{0.1(1.5)^2}a_0 + a_1(2) + a_2(2)^2 = e^{0.1(2)^2}Solve the equations to get the coefficients:a_0 = 0.3536a_1 = 4.0663a_2 = -3.5908Therefore, L_{2,0} (x) = 0.3536 + 4.0663x - 3.5908x^2Similarly, you can solve for L_{2,1} (x).To approximate f(1.25) using H5 (1.25) and H3 (1.25), substitute x = 1.25 into the respective polynomials:H5 (1.25) = 0.3536 + 4.0663(1.25) - 3.5908(1.25)^2 = 1.4571H3 (1.25) = 0.7444 + 1.8277(1
 

1. What is the meaning of "f(x)=e^(0.1x^2)" in this context?

The function f(x)=e^(0.1x^2) represents a mathematical equation where x is the independent variable and the value of f(x) is dependent on the value of x. The exponent 0.1x^2 indicates that the function is an exponential function with a base of e and a power of 0.1x^2.

2. What is the significance of using H5 and H3 in solving this function?

H5 and H3 refer to the fifth and third-order Hermite interpolation polynomials, respectively. These polynomials are used to approximate the value of the function at a given point and can help in finding the root of the function. Using these polynomials can make solving the function more efficient and accurate.

3. How do you calculate the error bounds for the solution obtained using H5 and H3?

The error bounds can be calculated using the Lagrange error bound theorem. This theorem states that the error in using an interpolation polynomial to approximate a function is proportional to the maximum value of the nth derivative of the function within the interval of interpolation. The error bounds can be calculated by finding the maximum value of the nth derivative of the function and using it in the formula for error bounds.

4. Can you explain the process of solving this function using H5 and H3?

To solve this function, we first compute the values of H5 and H3 at the given point. These values are then used to construct the Hermite interpolation polynomials. The next step is to find the root of the function by setting the Hermite interpolation polynomials equal to zero. The error bounds can also be calculated at this point using the Lagrange error bound theorem.

5. What are the advantages of using Hermite interpolation polynomials in solving this function?

Using Hermite interpolation polynomials can make solving this function more efficient and accurate. These polynomials take into account not only the value of the function at a given point but also the value of its derivatives. This can lead to a more precise approximation of the root of the function. Additionally, the error bounds can also be calculated, providing a measure of the accuracy of the solution obtained.

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