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001-Numerical Solution of Non Linear Equations

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    Numerical solution of non linear equations.

    Curve fitting

    Numerical solution of ordinary differential equations.

    Numerical solution of partial differential equations.

    Numerical solution of linear equations.

    Numerical integrations.

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    An equation in which one or more terms have a variable of

    degree 2 or higher is called a nonlinear equation. The non linear

    equation f (x) = 0 and we find the roots of this equation.

    Non Linear equation

    System of non linear equations

    A nonlinear system of equations contains at least one

    nonlinear equation.

    A system has one

    solution. A system has twosolutionsA system has manysolutions.

    A system has no

    solution.

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    It is one of the first numerical methods to find the root of anonlinear equation f(x) = 0 also called binary-searchmethod. The method is

    based on finding the root between two points.At least one root exists between the two points if the function is real,

    continuous, and changes sign. If the function does not change sign between

    the two points then there may not be any root for the equation between the

    two points.The steps to apply the bisection method to find the root of the equation

    are:

    1- Choose aand bfor the root such that f(a) f(b) < 0, or in other words, f (x)changes sign between aand b.2- Estimate the root xnsuch that xn= (an+ bn) / 2.If f(xn) = 0, then xnis the root of the equation. If f(xn) 0, f(xn) > 0 ,find the

    new estimate such that the mid point between a , xn. If f(xn) 0, f(xn) < 0,

    find the new estimate such that the mid point between xn, b.

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    It is the numerical method to find the root of a nonlinear equation

    f(x) = 0 also called method.

    The steps to apply the simple iteration method to find the root of the

    equation are:

    1- Choose x0.

    2- The function f(x) = 0 is transformed into equation x = g(x).

    3- Test the convergence

    4- Compute xn+1= g(xn)

    5- If ; end

    1)(xg 0

    xx n1n

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    It is the numerical method to find the root of a nonlinear equation

    f(x) = 0.

    The secant method is defined by the recurrence relation:)f(x

    )f(x)f(x

    xxxx n

    1nn

    1nnn1n

    It requires two initial values, x0and x1, which should ideally be

    chosen to lie close to the root.The steps to apply the Secant method to find the root of the equation

    are:1. Select x0and x1

    2. Evaluate f(x0) and f(x

    1)

    3. Evaluate xn+1

    4. If ; endxx n1n

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    It is the best numerical method and fast way to find the root of a

    nonlinear equation f(x) = 0.

    This method is defined by the recurrence relation:

    )(xf

    )f(xxxn

    nn1n

    )(xf

    )f(xxx

    n

    nn1n

    xx n1n

    1- From f (x) get f\ (x)

    2. Choose x0

    3. Evaluate

    4. If ; end

    The steps to apply the Newton-Raphson method to find the root of

    the equation are:

    and test the convergence 1.)](xf[

    )(xf)f(x2

    n

    00

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    Solve, using the Bisection method to find the positive root of the

    equation:f(x) = x3+ 4 x210 = 0.

    Let x =a = 1 f(1) = ,

    x = b =2 f(2) = +, then the root of this equation lies between [1, 2].

    f(xn)bnann

    2.3751.5210

    -1.796871.251.5110.162111.3751.51.252

    -0.848391.31251.3751.253

    -0.0033961.3649902351.3652343751.3647609412

    2

    bax nnn

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    Solve, using the simple iteration method to find the positive root :

    f(x) = x

    sin x = 0.25 correct to three decimal places.

    f(x) = xsin x - 0.25 = 0.

    1.5210x

    0.2530.841- 0.091- 0.25f(x)

    1362.02.1cos)( 0

    xg

    Let x0=1.2, x = sin x + 0.25.

    Then x = g(x) = sin x + 0.25.

    Test the convergence

    cosx(x)g

    43210n

    1.1721.1721.1731.1751.182xn+1

    Then xn+1= g(xn) =sin xn+0.25.

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    Solve, using the Secant method to find the positive root :

    f(x) = 0.18x3

    0.5 x2-2x +1 correct to four decimal places,where x0= 4, x1= 6.

    )f(x

    )f(x)f(x

    xxxx n

    1nn

    1nnn1n

    )125.018.0()125.018.0()125.018.0(

    xxxx 231

    2

    11323

    1nnn1n

    nnn

    nnn

    nnn

    xxxxxxxxx

    xn+1f(xn)xnf(xn-1)xn-1n

    4.52109.88006-3.480041

    4.7303-1.62874.52109.8800624.8513-0.59674.7303-1.62874.52103

    4.8368-0.08154.8513-0.59674.73034

    4.8373-0.00324.8368-0.08154.85135

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    1.x1.08(x)f

    2,xx0.54(x)f 2

    54321x

    1-3.48-4.64-3.56-1.32f(x)

    133.0)435.4(

    )86.3)(7225.1(

    )](xf[

    )(xf)f(x22

    n

    00

    Solve, using the Newton - Raphson method to find the positive root :

    f(x) = 0.18x3

    0.5 x2-2x +1 correct to four decimal places,

    Let x0= 4.5,

    Test the convergence

    .2xx0.54

    1x2x0.5x0.18xxn

    2

    n

    n

    2

    n

    3

    nn1n

    )(xf)f(xxx

    n

    nn1n

    210n

    4.83734.83824.8884xn+1

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    Let there be given a system of two equations in two unknowns,

    F (x, y) = 0,

    G (x, y) = 0.

    Let x = x0, y = y0be the approximate values of the root of this system.

    By using Newton-Raphsons method

    The general formula to get the required root is:

    ,

    GG

    FF

    GG

    FF

    xx

    )y,(xyx

    yx

    )y,(xy

    y

    n1n

    nn

    nn

    .

    GG

    FFGG

    FF

    yy

    )y,(xyx

    yx

    )y,(xx

    x

    n1n

    nn

    nn

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    Find the root of the system,

    F (x, y) = 4

    x2

    y2= 0,

    G (x, y) = 1exy = 0.

    Given that (x0, y0) = (1, -1.7). Two steps are required. Correct to 4D.

    We get:

    x,2x

    FFx

    ,2

    FF y

    yy

    ,exGG xx

    1.y

    GGy

    For (x0, y0) = (1, -1.7), we get:

    ,2Fx ,4.3F y ,7183.2Gx 1,Gy 0.11,F 0.0813.G

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    Then,

    0043.1

    17183.2

    4.32

    10183.0

    4.311.0

    1

    GG

    FF

    GG

    FF

    xx

    )y,(xyx

    yx

    )y,(xy

    y

    01

    nn

    00

    .7299.1

    17183.2

    4.32

    0183.07183.2

    11.02

    7.1

    GG

    FF

    GG

    FF

    yy

    )y,(xyx

    yx

    )y,(xx

    x

    01

    00

    00

    ,0086.2Fx

    For (x1, y1) = (1.0043, -1.7299), we get:

    ,4598.3F y,7300.2Gx 1,Gy ,00120.F .0010.0G

    ,0042.1

    17300.2

    4598.30086.2

    10001.04598.30012.0

    0043.1x2

    7296.1

    17300.2

    4598.30086.2

    0001.07300.2

    0012.00086.2

    7299.1y2


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