1. Solve by fixed-point iteration: x* – x – 0.12 = 0 a. Do 5 iterations with xo = 1 b. Do 5 iterations with x, = 0.5

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**Fixed-Point Iteration Exercise**

**Problem Statement:**

1. Solve by fixed-point iteration:

\[ x^4 - x - 0.12 = 0 \]

**Tasks:**

a. Perform 5 iterations with initial guess \( x_0 = 1 \)

b. Perform 5 iterations with initial guess \( x_0 = 0.5 \)

---

This exercise involves solving the given equation using the fixed-point iteration method. The fixed-point iteration is an numerical method for finding an approximation to the root of a real-valued function. With an initial guess \( x_0 \), the iteration proceeds as follows:

\[ x_{n+1} = g(x_n) \]

where \( g(x) \) is derived from the original equation \( f(x) = 0 \).

To apply the fixed-point iteration method for the given equation:

\[ x^4 - x - 0.12 = 0 \]

we need to re-arrange it into the form \( x = g(x) \). One possible rearrangement might be:

\[ x = \sqrt[4]{x + 0.12} \]

Then, use this form to perform the iterations as specified.

1. **First Initialization \( x_0 = 1 \)**
   - Perform 5 iterations:

\[
\begin{align*}
x_1 & = g(x_0) \\
x_2 & = g(x_1) \\
x_3 & = g(x_2) \\
x_4 & = g(x_3) \\
x_5 & = g(x_4)
\end{align*}
\]

2. **Second Initialization \( x_0 = 0.5 \)**
   - Perform 5 iterations:

\[
\begin{align*}
x_1 & = g(x_0) \\
x_2 & = g(x_1) \\
x_3 & = g(x_2) \\
x_4 & = g(x_3) \\
x_5 & = g(x_4)
\end{align*}
\]

This iterative process is used to approximate a solution to the equation. The results of the iterations will show how the approximations evolve towards the actual root of the equation with different initial guesses.
Transcribed Image Text:**Fixed-Point Iteration Exercise** **Problem Statement:** 1. Solve by fixed-point iteration: \[ x^4 - x - 0.12 = 0 \] **Tasks:** a. Perform 5 iterations with initial guess \( x_0 = 1 \) b. Perform 5 iterations with initial guess \( x_0 = 0.5 \) --- This exercise involves solving the given equation using the fixed-point iteration method. The fixed-point iteration is an numerical method for finding an approximation to the root of a real-valued function. With an initial guess \( x_0 \), the iteration proceeds as follows: \[ x_{n+1} = g(x_n) \] where \( g(x) \) is derived from the original equation \( f(x) = 0 \). To apply the fixed-point iteration method for the given equation: \[ x^4 - x - 0.12 = 0 \] we need to re-arrange it into the form \( x = g(x) \). One possible rearrangement might be: \[ x = \sqrt[4]{x + 0.12} \] Then, use this form to perform the iterations as specified. 1. **First Initialization \( x_0 = 1 \)** - Perform 5 iterations: \[ \begin{align*} x_1 & = g(x_0) \\ x_2 & = g(x_1) \\ x_3 & = g(x_2) \\ x_4 & = g(x_3) \\ x_5 & = g(x_4) \end{align*} \] 2. **Second Initialization \( x_0 = 0.5 \)** - Perform 5 iterations: \[ \begin{align*} x_1 & = g(x_0) \\ x_2 & = g(x_1) \\ x_3 & = g(x_2) \\ x_4 & = g(x_3) \\ x_5 & = g(x_4) \end{align*} \] This iterative process is used to approximate a solution to the equation. The results of the iterations will show how the approximations evolve towards the actual root of the equation with different initial guesses.
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