interpolation in numerical methods

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    NUMERICAL METHODS

    INTERPOLATION

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    INTRODUCTION TO INTERPOLATION

    IntroductionPolynomial Forms

    Linear and Quadratic interpolationInterpolation problemExistence and uniquenessLagrange interpolation polynomialNewtons Divided Difference method Properties of Divided Differences

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    INTERPOL TION

    DEFINITION

    3

    LET BE A CONTINEOUS FUNCTION DEFINED INTHE INTERVAL CONTAINING THE POINTS

    THE INTERPOLATION IS USED TO FINDTHE VALUE OF THE FUNCTION AT ANY PONIT INTHE INTERVAL OR

    INTERPOLATION MEANS TO FIND (APPROXIMATE)VALUES OF A FUNCTION FOR AN x BETWEENDIFFERENT x VALUES AT WHICH THE

    VALUES OFf(x)

    ARE GIVEN

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    INTERPOL TION

    EX MPLE

    4

    x 0 1 2

    f(x) 1 0 -1

    FIND:

    THE PROCESS OF CONSTRUCTION OFTO FIT A TABLE OF DATA POINTS IS

    CALLED CURVE FITTING

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    POLYNOMIAL FORMS

    POWER FORM

    SHIFT POWER FORM

    NEWTON FORM

    5

    n

    i

    n

    i j j

    jinn x xb x f x P 0 0

    )()()(

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    Examples of Polynomial InterpolationLinear Interpolation

    Given any two points,there is one polynomial oforder 1 that passesthrough the two points.

    Quadratic Interpolation

    Given any three points thereis one polynomial of order 2 that passes through thethree points.

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    LINEAR INTERPOLATIONGiven any two points,

    The line that interpolates the two points is

    Example :find a polynomial that interpolates (1,2) and (2,4)

    )(,,)(, 1100 x f x x f x

    x x x f 211224

    2)(1

    475

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    ExampleAn experiment is used to determinethe viscosity of water as afunction of temperature. Thefollowing table is generated

    Problem: Estimate the viscositywhen the temperature is 8 degrees.

    Temperature(degree)

    Viscosity

    0 1.792

    5 1.519

    10 1.308

    15 1.140

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    ExampleFind a polynomial that fit the data points

    exactly.

    tscoefficien

    polynomial:

    eTemperatur :

    viscosity:

    k a

    T

    V

    Linear Interpolation V(T)= 1.73 0.0422 TV(8)= 1.3924

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    Example

    10

    THE TABLE BELOW GIVES SQUARE ROOT FOR NTEGERS

    x 1 2 3 4 5f(x) 1 1.4142 1.7321 2 2.2361

    DETERMINE, THE SQUARE ROOT OF 2.5

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    The interpolation ProblemGiven a set of n+1 points,

    find an n th order polynomialthat passes through all points

    )(,....,,)(,,)(, 1100 nn x f x x f x x f x

    )( x f n

    ni for x f x f iin ,...,2,1,0)()(

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    Existence and UniquenessGiven a set of n+1 points

    Assumption are distinct real nos

    Theorem:

    There is a unique polynomial f n (x) oforder n

    such that

    ni for x f x f iin ,...,1,0)()(

    n x x x ,...,, 10

    )(,....,,)(,,)(, 1100 nn x f x x f x x f x

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    Quadratic InterpolationGiven any three points ,The polynomial that interpolates the three points is

    )(,)(,,)(, 221100 x f xand x f x x f x

    202

    01

    01

    12

    12

    2

    101

    011

    00

    1020102

    )()()()(

    )()(

    )(

    )(

    x xat x x

    x x x f x f

    x x x f x f

    b

    x xat x x

    x f x f b

    x xat x f b

    where

    x x x xb x xbb x f

    477

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    LAGRANGE INTERPOLATION

    Lagrange Interpolation Formula

    n

    i j j ji

    ji

    n

    iiin

    x x

    x x x

    x x f x f

    ,0

    0

    )(

    )()(

    486

    Let, denote distinct real nos and let bearbitrary real nos. The pts can be imagined to bedata values connected by a curve. Any fn satisfying the conditions:

    is called an interpolation fn. An interpolation fn is, therefore, a curvethat passes through the data pts.

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    Lagrange Interpolation

    ji

    ji x

    x

    ji

    i

    1

    0)(

    s polynomialordern tharecardinalsThe

    cardinalsthecalledare)(

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    EXAMPLE

    x 1/3 1/4 1y 2 -1 7

    )4/1)(3/1(27

    )1)(3/1(161)1)(4/1(182)(

    4/114/1

    3/113/1

    )(

    14/11

    3/14/13/1

    )(

    13/11

    4/13/14/1

    )(

    )()()()()()()(

    2

    12

    1

    02

    02

    21

    2

    01

    01

    20

    2

    10

    10

    2211002

    x x

    x x x x x P

    x x x x x x

    x x x x

    x

    x x x x x x

    x x x x

    x

    x x x x x x

    x x x x

    x

    x x f x x f x x f x P

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    EXAMPLE

    17

    , Where,

    EXAMPLE

    THE TABLE BELOW GIVES SQUARE ROOT FOR NTEGERS

    x 1 2 3 4 5f(x) 1 1.4142 1.7321 2 2.2361

    DETERMINE, THE SQUARE ROOT OF 2.5

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    NEWTONs INTERPOLATION POLYNOMIAL

    Given any n+1 points ,The polynomial that interpolates all points is

    )(,,...,)(,,)(, 1100 nn x f x x f x x f x

    .

    )()()()(

    )()()(

    ......)(

    202

    01

    01

    12

    12

    2

    101

    011

    00

    10102010

    on soand x xat x x x x

    x f x f x x

    x f x f

    a

    x xat x x

    x f x f a

    x xat x f a

    x x x xa x x x xa x xaa x f nnn

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    Divided Differences

    0

    1102110

    02

    1021210

    01

    0110

    ],...,,[],...,,[],...,,[

    ............

    DDorderSecond],[],[],,[

    DDorderfirst][][

    ],[

    DDorderzeroth)(][

    x x x x x f x x x f

    x x x f

    x x x x f x x f x x x f

    x x x f x f

    x x f

    x f x f

    k

    k k k

    k k

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    NEWTONs INTERPOLATION POLYNOMIAL

    Now

    ],...,,[

    ....

    ],,[

    )()()()(

    ],[)()(

    ][)(

    .. ....)(

    10

    2102

    01

    01

    12

    12

    2

    1001

    01

    1

    00

    10102010

    nn

    nnn

    x x x f b

    x x x f x x

    x x x f x f

    x x x f x f

    b

    x x f x x x f x f

    b

    x f x f b

    x x x xb x x x xb x xbb x f

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    NEWTONs INTERPOLATION POLYNOMIAL

    polynomial al erpolation

    differencedivided s Newtonasknown

    x x x x x f x f

    n

    i

    i

    j jin

    int

    '

    ],...,,[)( 0

    1

    010

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    EX MPLE

    22

    CONSTRUCT A POLYNOMIAL OF DEGREE TWO WHICHINTERPOLATES THE FOLLOWING SET OF POINTS.

    x 1 2 3

    f(x) 0 2 6

    ALSO, FIND THE VALUE OF F(2.5)

    f(2.5)=3.75

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    Divided Difference Tablex F[ ] F[ , ] F[ , , ] F[ , , ,]

    x 0 F[x0] F[x 0 ,x 1] F[x 0 ,x 1, x 2 ] F[x 0 ,x 1 ,x 2 ,x 3 ]

    x 1 F[x 1 ] F[x 1 ,x 2] F[x 1 ,x 2 ,x 3 ]

    x 2 F[x 2 ] F[x 2 ,x 3]

    x 3 F[x 3 ]

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    Divided Difference Tablef(x i )

    0 -5

    1 -3-1 -15

    i xx F[ ] F[ , ] F[ , , ]

    0 -5 2 -4

    1 -3 6

    -1 -15

    Entries of the divided differencetable are obtained from the datatable using simple operations

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    Divided Difference Tablef(x i )

    0 -51 -3

    -1 -15

    i xx F[ ] F[ , ] F[ , , ]

    0 -5 2 -4

    1 -3 6

    -1 -15

    The first two column of the

    table are the data columns

    Third column : first order differences

    Fourth column: Second order differences

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    Divided Difference Table

    0 -5

    1 -3-1 -15

    i yi xx F[ ] F[ , ] F[ , , ]0 -5 2 -4

    1 -3 6

    -1 -15

    201

    )5(3

    01

    0110

    ][][],[

    x x x f x f

    x x f

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    Divided Difference Table

    0 -5

    1 -3-1 -15

    i yi xx F[ ] F[ , ] F[ , , ]0 -5 2 -4

    1 -3 6

    -1 -15

    611

    )3(15

    12

    1221

    ][][],[

    x x x f x f

    x x f

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    Divided Difference Table

    0 -5

    1 -3-1 -15

    i yi xx F[ ] F[ , ] F[ , , ]0 -5 2 -4

    1 -3 6

    -1 -15

    4)0(1

    )2(6

    02

    1021210

    ],[],[],,[

    x x x x f x x f

    x x x f

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    Divided Difference Table

    0 -5

    1 -3-1 -15

    i yi xx F[ ] F[ , ] F[ , , ]0 -5 2 -4

    1 -3 6

    -1 -15

    )1)(0(4)0(25)(2 x x x x f

    f 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 )

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    Two Examples

    x y

    1 0

    2 3

    3 8

    Obtain the interpolating polynomials for the two examples

    x y

    2 3

    1 0

    3 8

    What do you observe?

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    Two Examples

    1

    )2)(1(1)1(30)(2

    2

    x

    x x x x P

    x Y

    1 0 3 1

    2 3 53 8

    x Y

    2 3 3 1

    1 0 43 8

    1

    )1)(2(1)2(33)(2

    2

    x

    x x x x P

    Ordering the points should not affect the interpolating polynomial

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    Properties of divided Difference

    ],,[],,[],,[ 012021210 x x x f x x x f x x x f

    Ordering the points should not affect the divided difference

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    ExampleFind a polynomial tointerpolate the data.

    x f(x)

    2 3

    4 5

    5 1

    6 6

    7 9

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    Example

    x f(x) f[ , ] f[ , , ] f[ , , , ] f[ , , , , ]2 3 1 -1.6667 1.5417 -0.6750

    4 5 -4 4.5 -1.83335 1 5 -16 6 37 9

    )6)(5)(4)(2(6750.0

    )5)(4)(2(5417.1)4)(2(6667.1)2(134 x x x x

    x x x x x x f

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    Examplefind a polynomial to interpolate

    both Newtons

    interpolation methodand Lagrangeinterpolation method

    must give the sameanswer

    x y

    0 1

    1 3

    2 2

    3 5

    4 4

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    Example 0 1 2 -3/2 1/6 -9/24

    1 3 -1 2 -4/3

    2 2 3 -2

    3 5 -1

    4 4

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    Interpolating Polynomial

    )3)(2)(1(249

    )2)(1(61

    )1(23

    )(21)(4

    x x x x

    x x x x x x x f

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    Interpolating Polynomial UsingLagrange Interpolation method

    343

    242

    141

    040

    434

    232

    131

    030

    424

    323

    121

    020

    414

    313

    212

    010

    404

    303

    202

    101

    4523)()(

    4

    3

    2

    1

    0

    43210

    4

    04

    x x x x

    x x x x

    x x x x

    x x x x

    x x x x

    x f x f i

    ii

    491

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    Inverse Interpolation

    g g g

    g

    y x f x

    y

    )(such thatFind

    andtableGiven the

    :Problem 0 x . .

    1 x n x

    0 y 1 y n yi x

    i y

    One approach :

    Use polynomial interpolation to obtain f n(x) to interpolate thedata then use Newtons method to find a solution to

    g g n y x f )(

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    Inverse Interpolation Alternative Approach

    0 x .

    .

    1 x n x

    0 y 1 y n y

    i x

    i y

    Inverse interpolation:

    1. Exchange the roles

    of x and y

    2. Perform polynomial

    Interpolation on the

    new table.

    3. Evaluate

    )( g n y f

    . .

    i y 0 y 1 y n y

    i x 0 x 1 x n x

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    Inverse InterpolationExample

    5.2)(such thatFind table.Given the

    :Problem

    g g x f x

    x 1 2 3y 3.2 2.0 1.6

    3.2 1 -.8333 1.04162.0 2 -2.5

    1.6 3

    2187.1)5.0)(7.0(0416.1)7.0(8333.01)5.2(

    )2)(2.3(0416.1)2.3(8333.01)(

    2

    2

    f

    y y y y f

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    -5 -4 -3 -2 -1 0 1 2 3 4 5-0.5

    0

    0.5

    1

    1.5

    2

    true function

    10 th order interpolating polynomial

    10 th order Polynomial Interpolation

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    Errors in polynomial Interpolation Theorem

    1

    )1(1)(n

    )1(4P(x)-f(x)

    Then points).endthe(including b][a,in

    pointsspacedequally1natf esinterpolatthatndegreeof polynomialany beP(x)Let

    b],[a,oncontinuousis(x)f

    such thatfunctiona bef(x)Let

    n

    n

    nab

    n M

    M f

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    Example 1

    910

    1

    )1(

    1034.19

    6875.1)10(4

    1P(x)-f(x)

    )1(4P(x)-f(x)

    9,1

    01

    [0,1.6875]intervalin the points)spacedequally01(using

    f(x)einterpolatto polynomialorderth9usewant toWe sin(x)f(x)

    n

    n

    nab

    n M

    n M

    n for f

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    Interpolation Error

    n

    iinn

    n

    n

    x x x x x x f x f f (x)

    x x x

    f

    010

    10

    ],,...,,[)(nodeanot

    any xforthen,...,,nodesat thef(x)functionthe

    esinterpolatn thatdegreeof polynomialtheis(x)If

    Not useful. Why?

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    Approximation of the Interpolation Error

    n

    iinnn

    nn

    n

    n

    x x x x x x f x f f (x)

    be x f x Let

    x x x f

    0110

    11

    10

    ],,...,,[)(

    byedapproximatiserrorioninterpolatThe

    pointadditionalan))(,(

    ,...,,nodesat thef(x)functiontheesinterpolatn thatdegreeof polynomialtheis(x)If

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    Divided Difference Theorem

    )(10

    10)(

    !

    1],...,,[

    b][a,someforthen b][a,in pointsdistinct1nanyare,...,,if and b][a,oncontinuousis

    nn

    nn

    f n

    x x x f

    x x x f If

    10],...,,[then

    norderof polynomialas)(

    10 ni x x x f

    i x f If

    i

    1 4 1 0 02 5 1 03 6 14 7

    x x f 3)(

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    SummaryThe interpolating polynomial is uniqueDifferent methods can be used to obtain it

    Newtons Divided difference

    Lagrange interpolationothers

    Polynomial interpolation can be sensitiveto data.BE CAREFUL when high orderpolynomials are used