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Interpolation(2) Numerical methods to CE Problems).pdf
1. Interpolation
โข The data are known to be very precise
โข To fit a curve or a series of curves that pass directly
through each of the points.
โข Estimate values between well-known discrete points.
nth-order polynomial general formula
โข ๐ ๐ฅ = ๐0 + ๐1๐ฅ + ๐2๐ฅ2
+ โฆ + ๐๐๐ฅ๐
2. โข Polynomial Interpolation
โข consists of determining the unique nth-order polynomial that fits
n+1 data points. This polynomial then provides a formula to
compute intermediate values.
โข Although there is one and only one nth-order polynomial that fits
n+1 points, there are a variety of mathematical formats in which
this polynomial can be expressed.
3. Polynomial Interpolation
โข Newtonโs Divided-Difference Interpolation Polynomials
โข The simplest form of
interpolation is to connect
two data points with a
straight line. This technique,
called linear interpolation.
8. f(x) 1 1.6 3.8 8.2 15.4
x 0 5 10 15 20
Find the value of f(x) at 3.
9. โข a strategy for improving the estimate by introducing some
curvature into the line connecting the points. If three data
points are available, this can be accomplished with a
second-order polynomial.
๐2 ๐ฅ = ๐0 + ๐1 ๐ฅ โ ๐ฅ0 + ๐2(๐ฅ โ ๐ฅ0)(๐ฅ โ ๐ฅ1)
Quadratic Interpolation
15. f(x) 1 1.6 3.8 8.2 15.4
x 0 5 10 15 20
Find the value of f(x) at 3 using quadratic interpolation
16. โข a strategy for improving the estimate by introducing some
curvature into the line connecting the points. n+1 data points
should be available to accomplish interpolation.
๐๐ ๐ฅ = ๐0 + ๐1 ๐ฅ โ ๐ฅ0 + โฏ + ๐๐ ๐ฅ โ ๐ฅ0 ๐ฅ โ ๐ฅ1 โฆ (๐ฅ โ ๐ฅ๐โ1)
General form of Newtonโs Interpolating Polynomials
19. โข The curvature shows improved value in the 3rd order or
cubic interpolation compared with the result obtained
using straight line and quadratic.
20. x 0 100 200 400 600 800 1000
f(x) 0 0.82436 1 0.73576 0.40601 0.19915 0.09158
โข Find the value of the function at x = 482 using
โข Linear Interpolation
โข Quadratic Interpolation
โข Find the value of the function at x = 140 using
โข Linear Interpolation
โข Quadratic Interpolation
21. โข a reformulation of the Newton polynomial that avoids the
computation of divided differences.
โข for a given set of points ๐ฅ๐, ๐ฆ๐ with no two ๐ฅ๐ values
equal, the Lagrange polynomial is the polynomial of the
lowest degree that assumes at each value ๐ฅ๐ the
corresponding value ๐ฆ๐, so that the functions coincide at
each point.
Lagrange Interpolating Polynomials