Alice has asked you to help her classify these functions based on their asymptotic growth rate. That is, she wants you to prove a tight big-Theta bound for each function by following these steps. i. Use algebra to simply the function for ease of analysis. Remember the goal of simplification is to isolate terms and identify the dominant term. For instance, we might want to expand (n + 1)² to n² +2n+1 to see that n² is the dominant term. ii. Use your intuition, the limit test, or algebra to come up with a good guess of a tight bound. For instance, after isolating n² as the dominant term we might guess our polynomial is in (n²). iii. Use the limit test or the definitions to prove that your guess is correct. Both methods can provide correct proofs, and its a good idea to practice both methods. Sometimes our guess is incorrect and we need to return to the previous step.

C++ for Engineers and Scientists
4th Edition
ISBN:9781133187844
Author:Bronson, Gary J.
Publisher:Bronson, Gary J.
Chapter6: Modularity Using Functions
Section6.1: Function And Parameter Declarations
Problem 11E
icon
Related questions
Question
Certainly! Below is the transcription of the image suitable for an educational website with detailed explanations.

---

### Mathematical Functions and Expressions

1. \( f_4(n) = (4n^2 + 25) \cdot (n^2 - 2n + 1) \)

   This is a function involving polynomials. It multiplies two quadratic expressions:
   - \(4n^2 + 25\)
   - \(n^2 - 2n + 1\)

2. \( f_5(n) = \log_2 \left( n^{n^3} \right) \)

   This function involves the logarithm (base 2) of an expression where \( n \) is raised to the power of \( n^3 \).

3. \( f_6(n) = \log_2 (n^2 + 5n - 3) \)

   This function calculates the logarithm (base 2) of a quadratic polynomial:
   - \( n^2 + 5n - 3 \)

4. \( f_7(n) = \log_2 (\log_2 n + 3) \)

   This function is a logarithm (base 2) of another logarithm (base 2) plus 3:
   - \( \log_2 n + 3 \)

5. \( f_8(n) = 2^{\frac{n}{2}} \)

   This function represents an exponential function where 2 is raised to the power of \( \frac{n}{2} \).

---

This set of functions and expressions illustrates a variety of mathematical operations, including polynomial multiplication, logarithms with different bases, and exponential functions. Each of these functions may be used in different contexts within mathematics and computer science, helping to describe complex relationships and behaviors.
Transcribed Image Text:Certainly! Below is the transcription of the image suitable for an educational website with detailed explanations. --- ### Mathematical Functions and Expressions 1. \( f_4(n) = (4n^2 + 25) \cdot (n^2 - 2n + 1) \) This is a function involving polynomials. It multiplies two quadratic expressions: - \(4n^2 + 25\) - \(n^2 - 2n + 1\) 2. \( f_5(n) = \log_2 \left( n^{n^3} \right) \) This function involves the logarithm (base 2) of an expression where \( n \) is raised to the power of \( n^3 \). 3. \( f_6(n) = \log_2 (n^2 + 5n - 3) \) This function calculates the logarithm (base 2) of a quadratic polynomial: - \( n^2 + 5n - 3 \) 4. \( f_7(n) = \log_2 (\log_2 n + 3) \) This function is a logarithm (base 2) of another logarithm (base 2) plus 3: - \( \log_2 n + 3 \) 5. \( f_8(n) = 2^{\frac{n}{2}} \) This function represents an exponential function where 2 is raised to the power of \( \frac{n}{2} \). --- This set of functions and expressions illustrates a variety of mathematical operations, including polynomial multiplication, logarithms with different bases, and exponential functions. Each of these functions may be used in different contexts within mathematics and computer science, helping to describe complex relationships and behaviors.
Alice has asked you to help her classify these functions based on their asymptotic growth rate. That is, she wants you to prove a tight big-Theta bound for each function by following these steps.

i. **Use algebra to simplify the function for ease of analysis.** Remember the goal of simplification is to isolate terms and identify the dominant term. For instance, we might want to expand \((n + 1)^2\) to \(n^2 + 2n + 1\) to see that \(n^2\) is the dominant term.

ii. **Use your intuition, the limit test, or algebra to come up with a good guess of a tight bound.** For instance, after isolating \(n^2\) as the dominant term we might guess our polynomial is in \(\Theta(n^2)\).

iii. **Use the limit test or the definitions to prove that your guess is correct.** Both methods can provide correct proofs, and it's a good idea to practice both methods. Sometimes our guess is incorrect and we need to return to the previous step.
Transcribed Image Text:Alice has asked you to help her classify these functions based on their asymptotic growth rate. That is, she wants you to prove a tight big-Theta bound for each function by following these steps. i. **Use algebra to simplify the function for ease of analysis.** Remember the goal of simplification is to isolate terms and identify the dominant term. For instance, we might want to expand \((n + 1)^2\) to \(n^2 + 2n + 1\) to see that \(n^2\) is the dominant term. ii. **Use your intuition, the limit test, or algebra to come up with a good guess of a tight bound.** For instance, after isolating \(n^2\) as the dominant term we might guess our polynomial is in \(\Theta(n^2)\). iii. **Use the limit test or the definitions to prove that your guess is correct.** Both methods can provide correct proofs, and it's a good idea to practice both methods. Sometimes our guess is incorrect and we need to return to the previous step.
Expert Solution
steps

Step by step

Solved in 4 steps with 3 images

Blurred answer
Knowledge Booster
Bounded summation
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, computer-science and related others by exploring similar questions and additional content below.
Similar questions
  • SEE MORE QUESTIONS
Recommended textbooks for you
C++ for Engineers and Scientists
C++ for Engineers and Scientists
Computer Science
ISBN:
9781133187844
Author:
Bronson, Gary J.
Publisher:
Course Technology Ptr
C++ Programming: From Problem Analysis to Program…
C++ Programming: From Problem Analysis to Program…
Computer Science
ISBN:
9781337102087
Author:
D. S. Malik
Publisher:
Cengage Learning
COMPREHENSIVE MICROSOFT OFFICE 365 EXCE
COMPREHENSIVE MICROSOFT OFFICE 365 EXCE
Computer Science
ISBN:
9780357392676
Author:
FREUND, Steven
Publisher:
CENGAGE L