(a) Use the golden section method to find the minimizer of the function in Eq. (1) within interval [1,3]. Estimate in advance how many iterations are needed so that the range is smaller than 0.2. Write down your procedure performed and the results in each step. 1 f(x) = r* +x³ – 4x².

Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter7: Analytic Trigonometry
Section7.6: The Inverse Trigonometric Functions
Problem 91E
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I need A,B, and C part 

2. Hint: you may need to use a calculator.
(a) Use the golden section method to find the minimizer of the function in Eq. (1) within interval
[1,3]. Estimate in advance how many iterations are needed so that the range is smaller than
0.2. Write down your procedure performed and the results in each step.
f(x) =
+x² – 4x?. ed
(b) Use the secant method to find a minimizer of the function in Eq. (1) with initial points x° = 1
and x' = 1.1. Write down the first five iterations, including the procedure performed and the
results obtained in each step.
(c) Use the steepest gradient descent method (a.k.a. gradient descent with exact line search) to
find the minimizer of
f(x1,x2) = x} +x3,
from an initial point (1, 1). Detail the procedure and the results in each iteration for the first three
iterations.
(d) Let x = 1/2(2*), and what is the limit of x as k → 00? What is the order of converge for xk?
(e) Let x E R" and f(x) = x' Qx – b' x where Q is a symmetric and positive definite matrix
and b is a n-dimensional vector. Suppose that we use the steepest gradient descent algorithm
(a.k.a. gradient descent with exact line search) to find the minimizer of f(x):
x*+! = x* - agVf(x)
where
arg min o (a) = f(x* - aVf(x*)).
Ok =
Write down the gradient Vf(x). Derive the expression of function or(a) specifically for f(x) =
x' Qx-b'x and simplify it if possible. Derive the solution to Eq. (2) and show that the resulting
a satisfies the following condition:
f(x*) +(1 – c)a&Vf(xt)" pk S f(x* + %Pk) < f(x*) +ca&Vf(x*)" pk
Pk:
with 0 <c< 1/2 and pk = -Vf(x*).
Transcribed Image Text:2. Hint: you may need to use a calculator. (a) Use the golden section method to find the minimizer of the function in Eq. (1) within interval [1,3]. Estimate in advance how many iterations are needed so that the range is smaller than 0.2. Write down your procedure performed and the results in each step. f(x) = +x² – 4x?. ed (b) Use the secant method to find a minimizer of the function in Eq. (1) with initial points x° = 1 and x' = 1.1. Write down the first five iterations, including the procedure performed and the results obtained in each step. (c) Use the steepest gradient descent method (a.k.a. gradient descent with exact line search) to find the minimizer of f(x1,x2) = x} +x3, from an initial point (1, 1). Detail the procedure and the results in each iteration for the first three iterations. (d) Let x = 1/2(2*), and what is the limit of x as k → 00? What is the order of converge for xk? (e) Let x E R" and f(x) = x' Qx – b' x where Q is a symmetric and positive definite matrix and b is a n-dimensional vector. Suppose that we use the steepest gradient descent algorithm (a.k.a. gradient descent with exact line search) to find the minimizer of f(x): x*+! = x* - agVf(x) where arg min o (a) = f(x* - aVf(x*)). Ok = Write down the gradient Vf(x). Derive the expression of function or(a) specifically for f(x) = x' Qx-b'x and simplify it if possible. Derive the solution to Eq. (2) and show that the resulting a satisfies the following condition: f(x*) +(1 – c)a&Vf(xt)" pk S f(x* + %Pk) < f(x*) +ca&Vf(x*)" pk Pk: with 0 <c< 1/2 and pk = -Vf(x*).
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