Numerical Analysis: Linearity of Divided Differences and Interpolation Polynomials - Prof., Assignments of Mathematical Methods for Numerical Analysis and Optimization

Solutions to writing assignments in a numerical analysis course, specifically addressing the linearity of divided differences and the derivation of the newton and lagrange interpolation forms. It includes the use of taylor expansion and the derivation of coefficients for interpolation polynomials.

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CHE/COSC/MATH 4340-01 Numerical Analysis
Solution of Writing Assignment 06
Due Date: Thursday, 03/31/09
Problem 29, pp. 150 We will show that divided differences are linear maps by induction. Let αand β
be two constants. For n=1, we have
(αf+βg)[x0,x1] = (αf+βg)(x1)(αf+βg)(x0)
x1x0
(by definition of divided difference)
=αf(x1) + βg(x1)αf(x0)βg(x0)
x1x0
(by linearity of the combination)
=αf(x1)f(x0)
x1x0
+βg(x1)g(x0)
x1x0
=αf[x0,x1] + βg[x0,x1].
(0.1)
This shows that divided differences are linear maps for n=1. Next, assume that it is true for n1, i.e.,
(αf+βg)[xi,xi+1,· · · ,xi+n1] = αf[xi,xi+1,· · · ,xi+n1] + βg[xi,xi+1,· · · ,xi+n1].(0.2)
Using this assumption, we will show it is true for n. To this end, we write
(αf+βg)[x0,x1,· · · ,xn]
=(αf+βg)[x1,x2,· · · ,xn](αf+βg)[x0,x1,· · · ,xn1]
xnx0
=αf[x1,x2,· · · ,xn] + βg[x1,x2,· · · ,xn]αf[x0,x1,· · · ,xn1]βg[x0,x1,· · · ,xn1]
xnx0
,
(0.3)
where we have used the assumption for n1 on the last line. Continuing on by rearranging terms, we
see that
(αf+βg)[x0,x1,· · · ,xn]
=αf[x1,x2,· · · ,xn]f[x0,x1,· · · ,xn1]
xnx0
+βg[x1,x2,· · · ,xn]g[x0,x1,· · · ,xn1]
xnx0
=αf[x0,x1,· · · ,xn] + βg[x0,x1,· · · ,xn],
(0.4)
which confirms that divided differences are linear maps for n.
1
pf3
pf4

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CHE/COSC/MATH 4340-01 Numerical Analysis

Solution of Writing Assignment 06 Due Date: Thursday, 03/31/

Problem 29, pp. 150 We will show that divided differences are linear maps by induction. Let α and β be two constants. For n = 1, we have

(α f + β g)[x 0 , x 1 ] = (α f + β g)(x 1 ) − (α f + β g)(x 0 ) x 1 − x 0

(by definition of divided difference)

=

α f (x 1 ) + β g(x 1 ) − α f (x 0 ) − β g(x 0 ) x 1 − x 0 (by linearity of the combination)

= α f (x 1 ) − f (x 0 ) x 1 − x 0

  • β g(x 1 ) − g(x 0 ) x 1 − x 0 = α f [x 0 , x 1 ] + β g[x 0 , x 1 ].

This shows that divided differences are linear maps for n = 1. Next, assume that it is true for n − 1, i.e.,

(α f + β g)[xi, xi+ 1 , · · · , xi+n− 1 ] = α f [xi, xi+ 1 , · · · , xi+n− 1 ] + β g[xi, xi+ 1 , · · · , xi+n− 1 ]. (0.2)

Using this assumption, we will show it is true for n. To this end, we write

(α f + β g)[x 0 , x 1 , · · · , xn]

= (α f + β g)[x 1 , x 2 , · · · , xn] − (α f + β g)[x 0 , x 1 , · · · , xn− 1 ] xn − x 0 = α f [x 1 , x 2 , · · · , xn] + β g[x 1 , x 2 , · · · , xn] − α f [x 0 , x 1 , · · · , xn− 1 ] − β g[x 0 , x 1 , · · · , xn− 1 ] xn − x 0

where we have used the assumption for n − 1 on the last line. Continuing on by rearranging terms, we see that

(α f + β g)[x 0 , x 1 , · · · , xn]

= α f [x 1 , x 2 , · · · , xn] − f [x 0 , x 1 , · · · , xn− 1 ] xn − x 0

  • β g[x 1 , x 2 , · · · , xn] − g[x 0 , x 1 , · · · , xn− 1 ] xn − x 0 = α f [x 0 , x 1 , · · · , xn] + β g[x 0 , x 1 , · · · , xn],

which confirms that divided differences are linear maps for n.

Problem 35 pp. 150 Newton form for interpolating polynomial p 2 (x) is

p 2 (x) = f (x 0 ) + f [x 0 , x 1 ](x − x 0 ) + f [x 0 , x 1 , x 2 ](x − x 0 )(x − x 1 ). (0.5)

Using definition of divided differences, we write

p 2 (x) = f (x 0 ) + f [x 0 , x 1 ](x − x 0 ) + f [x 0 , x 1 , x 2 ](x − x 0 )(x − x 1 )

= f (x 0 ) + ( f (x 1 ) − f (x 0 )) x − x 0 x 1 − x 0

  • ( f [x 1 , x 2 ] − f [x 0 , x 1 ]) (x − x 0 )(x − x 1 ) x 2 − x 0 = f (x 0 ) + ( f (x 1 ) − f (x 0 )) x − x 0 x 1 − x 0

( (^) f (x 2 ) − f (x 1 ) x 2 − x 1

f (x 1 ) − f (x 0 ) x 1 − x 0

)(x − x 0 )(x − x 1 ) x 2 − x 0 = f (x 0 )m 0 (x) + m 1 (x) f (x 1 ) + m 2 (x) f (x 2 ),

where

m 0 (x) = 1 − x − x 0 x 1 − x 0

(x − x 0 )(x − x 1 ) (x 1 − x 0 )(x 2 − x 0 ) m 1 (x) = x − x 0 x 1 − x 0

(x − x 0 )(x − x 1 ) (x 2 − x 1 )(x 2 − x 0 )

(x − x 0 )(x − x 1 ) (x 1 − x 0 )(x 2 − x 0 ) m 2 (x) = (x − x 0 )(x − x 1 ) (x 2 − x 0 )(x 2 − x 1 )

If we can show that mi(x) = li(x), then we have confirmed that Newton form is the same as Lagrange form. Obviously m 2 (x) = l 2 (x). Furthermore,

m 0 (x) = 1 − x − x 0 x 1 − x 0

(x − x 0 )(x − x 1 ) (x 1 − x 0 )(x 2 − x 0 ) = x 1 − x 0 − x + x 0 x 1 − x 0

(x − x 0 )(x − x 1 ) (x 0 − x 1 )(x 0 − x 2 ) = x − x 1 x 0 − x 1

(x − x 0 )(x − x 1 ) (x 0 − x 1 )(x 0 − x 2 ) = x − x 1 x 0 − x 1

x − x 0 x 0 − x 2

x − x 1 x 0 − x 1

(x 0 −^ x 2 +^ x^ −^ x 0 x 0 − x 2

(x − x 1 )(x − x 2 ) (x 0 − x 1 )(x 0 − x 2 ) = l 0 (x).

Similar derivation shows that m 1 (x) = l 1 (x).

Problem 10, pp. 176

a. Suppose f (x) is interpolated by a polynomial of degree 2, i.e., p 2 (x) = c 0 + c 1 (x − x 0 ) + c 2 (x − x 0 )(x − x 1 ) with

f (x 0 ) = p 2 (x 0 ) = c 0 f (x 1 ) = p 2 (x 1 ) = c 0 + c 1 (x 1 − x 0 ) = c 0 + hc 1 f (x 2 ) = p 2 (x 2 ) = c 0 + c 1 (x 2 − x 0 ) + c 2 (x 2 − x 0 )(x 2 − x 1 ) = c 0 + c 1 (x 2 − x 1 + x 1 − x 0 ) + c 2 (x 2 − x 1 + x 1 − x 0 )(x 2 − x 1 ) = c 0 + c 1 ( 1 + α)h + c 2 ( 1 + α)αh^2.

These equations give

c 0 = f (x 0 )

c 1 = f (x 1 ) − f (x 0 ) h c 2 = f (x 2 ) − f (x 0 ) − ( f (x 1 ) − f (x 0 ))( 1 + α) ( 1 + α)αh^2

h^2

[ (^) f (x 2 ) ( 1 + α)α

f (x 1 ) α

f (x 0 ) α

( 1 + α)

)]

h^2

[ (^) f (x 0 ) 1 + α

f (x 1 ) α

f (x 2 ) ( 1 + α)α

]

Now we set f ′′(x) ≈ p′′ 2 (x) = 2 c 2.

b. Assume f ′′(x) ≈ A f (x 0 ) + B f (x 1 ) +C f (x 2 ), and assume that this approximation is exact for poly- nomial of degree 2. Thus it is exact for 1, (x − x 1 ) and (x − x 1 )^2. To this end we get

A + B +C = 0 −hA + 0 + αhC = 0 h^2 A + 0 + α^2 h^2 C = 2.

From the second equation we get A = αC, substitute to third equation to get h^2 (α + α^2 )C = 2, from which we get C =

h^2 α( 1 + α)

, and thus A =

h^2 ( 1 + α)

. Substitute the resulting A and C to

the first equation to give B =

h^2 α