Numerical Differentiation Forward, Backward, Central Differences Lagrange Estimation.
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Transcript of Numerical Differentiation Forward, Backward, Central Differences Lagrange Estimation.
Numerical Derivatives
In this section we will see how to estimate the value of a derivative based on knowing only certain function values. This is typical for many applications not to know the exact function you are dealing with but rather a set of values for it.
The methods that are used tend to separate themselves into methods for values of the independent variables that are equally spaced and those that are not.
Equally Spaced Data Points
If we consider three values for x: xi-1, xi, and xi+1 with xi-1 < xi < xi+1 we can form the slopes of various secant lines with the corresponding y values yi-1=f(xi-1), yi=f(xi) and yi+1=f(xi+1) to estimate the derivative.
xi-1 xi xi+1
yi-1
yi
yi+1
f(x)
Forward Differences
ii
iii
ii
iii
xx
yyxf
xx
yyxf
1
1
1
11
'
'
Backward Differences
ii
iii
ii
iii
xx
yyxf
xx
yyxf
1
1
1
11
'
'
xi-1 xi xi+1
yi-1
yi
yi+1
f(x)Central Difference
11
11'
ii
iii xx
yyxf
If we assume the data are evenly spaced so that xi-xi-1 = h = xi+1-xi the formulas below become:
Forward Difference Backward Difference Central Difference
h
yyxf ii
i
1'
h
yyxf ii
i
1'
h
yyxf ii
i 2' 11
If you look in each of these formulas we are only using two pieces of information. This means we are probably not as accurate as we can be. What if we would like to estimate the value of the derivative at xi-1 but make use of all three data points?
Three-Point Difference Formulas for Derivatives (Evenly spaced points)
The two formulas below estimate the value of the derivatives at the endpoints making use of all three points most often giving a more accurate value for the derivative.
Three-Point Forward Difference
11
111
34'
ii
iiii xx
yyyxf
Three-Point Backward Difference
11
111
43'
ii
iiii xx
yyyxf
Both of these formulas come from writing out the Lagrange Interpolating polynomial for these three points, taking the derivative then plugging in the value you want.
))((
))((
))((
))((
))((
))(()(
111
11
11
11
111
11
iiii
iii
iiii
iii
iiii
iii xxxx
xxxxy
xxxx
xxxxy
xxxx
xxxxyxp
))((
2
))((
2
))((
2)('
111
11
11
11
111
11
iiii
iii
iiii
iii
iiii
iii xxxx
xxxy
xxxx
xxxy
xxxx
xxxyxp
))((
2
))((
2
))((
2)('
111
11
11
11
111
11
iiii
iii
iiii
iii
iiii
iii xxxx
xxxy
xxxx
xxxy
xxxx
xxxyxp
))((
2
))((
2
))((
2)('
111
111
11
111
111
1111
iiii
iiii
iiii
iiii
iiii
iiiii xxxx
xxxy
xxxx
xxxy
xxxx
xxxyxp
))(())(())(()('
111
11
11
11
111
11111
iiii
iii
iiii
iii
iiii
iiiiii xxxx
xxy
xxxx
xxy
xxxx
xxxxyxp
Consider the data being equally spaced by h:
))(())((
2
))((
2)('
1111
1111111
iiiii
iiiii
iiiiii xxxx
hy
xxxx
hy
xxxx
hhyxp
h
yyy
h
y
h
y
h
y
h
hy
h
hy
h
hyxp iiiiii
iiii 2
43
2
2
2
3
2
2
2
3)(' 1111
212211
11
111
34'
ii
iiii xx
yyyxf
Unequally-Spaced Data Points
In many situations the data points are not equally spaced. To estimate the value of the derivative we use the Lagrange Polynomial just like before. In this situation notice that the derivative can be estimated at any point.
))((
))((
))((
))((
))((
))(()(
111
11
11
11
111
11
iiii
iii
iiii
iii
iiii
iii xxxx
xxxxy
xxxx
xxxxy
xxxx
xxxxyxp
))((
2
))((
2
))((
2)(')('
111
11
11
11
111
11
iiii
iii
iiii
iii
iiii
iii xxxx
xxxy
xxxx
xxxy
xxxx
xxxyxpxf
))(())(())(()(
111
112
111
11112
111
112
1iiii
iiiii
iiii
iiiii
iiii
iiiii xxxx
xxxxxxxy
xxxx
xxxxxxxy
xxxx
xxxxxxxyxp
Higher Order Derivatives
All the previous formulas we have derived are to estimate the first derivative. What if we want to estimate the second derivative?
Second derivative estimates rely on writing out the Taylor Series for a modified version of the function f(x). We write out the Taylor Series for f(x+h) treating x as a constant and h as the variable and expanding at the point 0.
4)4(
32
!4
)(
!3
)('''
!2
)('')(')()( h
xfh
xfh
xfhxfxfhxf
4)4(
32
!4
)(
!3
)('''
!2
)('')(')()( h
xfh
xfh
xfhxfxfhxf
add !
4)4(
2
!4
)(2
!2
)(''2)(2)()( h
xfh
xfxfhxfhxf
2)4(
2 !4
)(2)('')()(2)(
1h
xfxfhxfxfhxf
h
4)4(
2
!4
)(2)('')()(2)( h
xfhxfhxfxfhxf
Example:
Find estimates for the derivative with the data set given to the right. We notice the x values are evenly spaced.
Two-Point Estimates:
i xi yi
1 3 1
2 5 4
3 7 3
2
1
57
43)5('
2
3
35
14)3('
f
f
2
1
57
43)7('
2
3
35
14)5('
f
f
Forward Backward
2
1
4
2
37
13)5('
f
Central
Three Point Estimates:
2
5
4
10
37
)1(3)4(43)3('
f2
3
4
6
37
)1(1)4(4)3(3)7('
f
Forward Backward
14
41)4(23
2
1)5(''
2
f
Second Derivative
(h=2)