Computer Science/Numerical Methods/ Iteration method ( with it’s convergence condition).
Contents
- 1 2. Convergence Condition
- 1.1 Explanation of Convergence Condition
- 1.2 3. Example of Iteration Method
- 1.3 Find the root of x3+x−1=0x^3 + x – 1 = 0x3+x−1=0 using iteration method.
- 1.4 4. Advantages and Disadvantages
- 1.5 Computer Science/Numerical Methods/ Iteration method ( with it’s convergence condition).
- 1.6 Numerical Methods for Solving Systems of Nonlinear …
- 1.7 MCA-08 / BCA-12: Computer Oriented Numerical Methods
- 1.8 B.Tech 4th Semester MATHEMATICS- …
- 1.9 Numerical Analysis
- 2 Iteration Method in Numerical Methods
- 3 Summary Table:
- 4 Want More?
Iteration Method in Numerical Methods
The Iteration Method is a technique used to find the root of an equation f(x)=0f(x) = 0. It is based on approximating the root through successive iterations, refining the value until it reaches the desired accuracy.
1. General Form of Iteration Method
The given equation f(x)=0f(x) = 0 is rewritten in the form:
x=g(x)x = g(x)
where g(x)g(x) is a function derived from f(x)f(x).
An initial guess x0x_0 is selected, and the next approximation is obtained using the formula:
xn+1=g(xn)x_{n+1} = g(x_n)
This process continues until the absolute difference between successive approximations is less than a predefined tolerance ϵ\epsilon, i.e.,
∣xn+1−xn∣<ϵ|x_{n+1} – x_n| < \epsilon
2. Convergence Condition
For the iteration method to converge to a root α\alpha, the function g(x)g(x) must satisfy:
∣g′(α)∣<1| g'(\alpha) | < 1
where g′(α)g'(\alpha) is the derivative of g(x)g(x) evaluated at the root α\alpha.
Explanation of Convergence Condition
- If ∣g′(x)∣<1|g'(x)| < 1 in the neighborhood of the root, the successive approximations get closer to the root.
- If ∣g′(x)∣>1|g'(x)| > 1, the method diverges, meaning it moves away from the actual root.
3. Example of Iteration Method
Find the root of x3+x−1=0x^3 + x – 1 = 0 using iteration method.
Step 1: Rewrite in the form x=g(x)x = g(x)
x=1−x3x = 1 – x^3
Step 2: Select an initial guess
Let x0=0.5x_0 = 0.5.
Step 3: Apply the iteration formula
Using xn+1=1−xn3x_{n+1} = 1 – x_n^3,
x1=1−(0.5)3=1−0.125=0.875x_1 = 1 – (0.5)^3 = 1 – 0.125 = 0.875 x2=1−(0.875)3=1−0.6699=0.3301x_2 = 1 – (0.875)^3 = 1 – 0.6699 = 0.3301 x3=1−(0.3301)3=1−0.0359=0.9641x_3 = 1 – (0.3301)^3 = 1 – 0.0359 = 0.9641
This process continues until convergence.
4. Advantages and Disadvantages
Advantages:
- Simple and easy to implement.
- Does not require complex calculations like derivatives.
Disadvantages:
- May not always converge.
- Requires a good initial guess.
If you need more examples or explanations, let me know!
Computer Science/Numerical Methods/ Iteration method ( with it’s convergence condition).
Numerical Methods for Solving Systems of Nonlinear …
MCA-08 / BCA-12: Computer Oriented Numerical Methods
B.Tech 4th Semester MATHEMATICS- …
Numerical Analysis
Here’s a complete and easy-to-understand explanation of the Iteration Method in Numerical Methods (especially useful for Computer Science or Engineering students), along with its convergence condition:
Iteration Method in Numerical Methods
What is the Iteration Method?
The Iteration Method (also called the Successive Approximation Method or Fixed Point Iteration Method) is used to find the root of a non-linear equation:
f(x)=0f(x) = 0
We rewrite this into the form:
x=g(x)x = g(x)
Then we apply the iteration:
xn+1=g(xn)x_{n+1} = g(x_n)
We continue this process until the difference ∣xn+1−xn∣|x_{n+1} – x_n| is less than a desired tolerance.
Steps to Apply Iteration Method:
- Rearrange f(x)=0f(x) = 0 into x=g(x)x = g(x)
- Choose an initial guess x0x_0
- Compute:
x1=g(x0),x2=g(x1),…x_1 = g(x_0), \quad x_2 = g(x_1), \quad \dots
- Stop when:
∣xn+1−xn∣<ε|x_{n+1} – x_n| < \varepsilon(where ε\varepsilon is a small tolerance like 0.0001)
Convergence Condition
For the iteration method to converge to a root α\alpha, the function g(x)g(x) must satisfy:
- α=g(α)\alpha = g(\alpha) (the fixed point)
- Convergence condition:
∣g′(α)∣<1|g'(\alpha)| < 1
This means the derivative of g(x)g(x) near the root should be less than 1 in absolute value.
If ∣g′(x)∣>1|g'(x)| > 1, the method diverges.
Example Problem:
Find the root of the equation:
x3+x−1=0x^3 + x – 1 = 0
Let’s take:
x=11+x2x = \frac{1}{1 + x^2}
x1=11+(0.5)2=0.8x_1 = \frac{1}{1 + (0.5)^2} = 0.8 x2=11+(0.8)2≈0.6098x_2 = \frac{1}{1 + (0.8)^2} ≈ 0.6098 x3=11+(0.6098)2≈0.728x_3 = \frac{1}{1 + (0.6098)^2} ≈ 0.728
… and continue until convergence.
Advantages of Iteration Method:
- Simple to understand and implement
- Needs only one initial guess
Limitations:
- Convergence is not guaranteed unless condition ∣g′(x)∣<1|g'(x)| < 1 holds
- May converge slowly
Summary Table:
Term | Description |
---|---|
Equation Form | x=g(x)x = g(x) |
Iteration Rule | xn+1=g(xn)x_{n+1} = g(x_n) |
Convergence | If ( |
Divergence | If ( |
Stopping Rule | ( |
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