Numirical Analysis
Presented by : Lecturer Viyan J.Jalal
Prepared by : Muhammed M.Saleh
12/2/2017Muhammed Mehdi
1
Roots Of Equations
 A root or solutions of equation f(x)=0 are the values of x for which the equation
holds true. Sometimes roots of equations are called as zeros of the equation.
 Numerical methods for finding roots of equations can often be easily programmed.
12/2/2017Muhammed Mehdi
2
Root Finding Methods
 Bisection Methods.
 False position methods.
 Secant methods.
 Newton-Raphson Method.
 Fixed-point method.
 Aitken method .
12/2/2017Muhammed Mehdi
3
False Position Method Example:
 Consider finding the root of f(x) = x2 - 3. Let εstep = 0.01, εabs = 0.01 and start
with the interval [1, 2].
12/2/2017Muhammed Mehdi
4
Newton Raphson
 If the initial guess at the root is xi,
a tangent can be extended from
the point {xi,x(xi)}. The point
where this tangent crosses the x-
axis usually represents an
improved estimate of the root.
12/2/2017Muhammed Mehdi
5
Example
 F(x)=x^3-x^2-2x+1, Xo=0 ,eps 10^-6
ans=(0.4450)
12/2/2017Muhammed Mehdi
6
Aitken methods.
 To accelerate the convergence we compute two values D1 & D2:
𝐷1 = 𝑥0 − 𝑥1
𝐷2 = 𝑥0 − 2𝑥1 + 𝑥2
𝑋∗ = Xo −
𝐷1
2
𝐷2
12/2/2017Muhammed Mehdi
7
Example
 F(x)=(x+10)^(1/4) , Po=4 , eps=10^-6 find the root ?
12/2/2017Muhammed Mehdi
8
Useful Source
 Google-wikipida
 Lecture course
 https://www.google.iq/search?hl=ar&site=imghp&tbm
12/2/2017Muhammed Mehdi
9
12/2/2017Muhammed Mehdi
10

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Numirical analysis

  • 1. Numirical Analysis Presented by : Lecturer Viyan J.Jalal Prepared by : Muhammed M.Saleh 12/2/2017Muhammed Mehdi 1
  • 2. Roots Of Equations  A root or solutions of equation f(x)=0 are the values of x for which the equation holds true. Sometimes roots of equations are called as zeros of the equation.  Numerical methods for finding roots of equations can often be easily programmed. 12/2/2017Muhammed Mehdi 2
  • 3. Root Finding Methods  Bisection Methods.  False position methods.  Secant methods.  Newton-Raphson Method.  Fixed-point method.  Aitken method . 12/2/2017Muhammed Mehdi 3
  • 4. False Position Method Example:  Consider finding the root of f(x) = x2 - 3. Let εstep = 0.01, εabs = 0.01 and start with the interval [1, 2]. 12/2/2017Muhammed Mehdi 4
  • 5. Newton Raphson  If the initial guess at the root is xi, a tangent can be extended from the point {xi,x(xi)}. The point where this tangent crosses the x- axis usually represents an improved estimate of the root. 12/2/2017Muhammed Mehdi 5
  • 6. Example  F(x)=x^3-x^2-2x+1, Xo=0 ,eps 10^-6 ans=(0.4450) 12/2/2017Muhammed Mehdi 6
  • 7. Aitken methods.  To accelerate the convergence we compute two values D1 & D2: 𝐷1 = 𝑥0 − 𝑥1 𝐷2 = 𝑥0 − 2𝑥1 + 𝑥2 𝑋∗ = Xo − 𝐷1 2 𝐷2 12/2/2017Muhammed Mehdi 7
  • 8. Example  F(x)=(x+10)^(1/4) , Po=4 , eps=10^-6 find the root ? 12/2/2017Muhammed Mehdi 8
  • 9. Useful Source  Google-wikipida  Lecture course  https://www.google.iq/search?hl=ar&site=imghp&tbm 12/2/2017Muhammed Mehdi 9