Knowee
Questions
Features
Study Tools

f(n) = (log n)^2023 Write a correct asymptotic upper bound for each of the above.

Question

f(n) = (log n)^2023

Write a correct asymptotic upper bound for each of the above.

🧐 Not the exact question you are looking for?Go ask a question

Solution

To find a correct asymptotic upper bound for the function f(n)=(logn)2023 f(n) = (\log n)^{2023} , we will analyze the growth of this function as n n approaches infinity.

Step 1: Break Down the Problem

  1. Understand the function f(n)=(logn)2023 f(n) = (\log n)^{2023} .
  2. Determine an expression that serves as an asymptotic upper bound for f(n) f(n) .

Step 2: Relevant Concepts

  • The notation O(g(n)) O(g(n)) is used to denote an asymptotic upper bound. This means that f(n) f(n) grows at most as quickly as g(n) g(n) for large values of n n .
  • We need to find a suitable g(n) g(n) for (logn)2023 (\log n)^{2023} .

Step 3: Analysis and Detail

  1. The logarithmic function logn \log n grows slower than any polynomial function of n n as n n increases.
  2. Thus, the function (logn)2023 (\log n)^{2023} will grow slower than any polynomial function of n n . For instance, we can consider functions like nϵ n^\epsilon for any small ϵ>0 \epsilon > 0 .
  3. We can see that as n n \to \infty : (logn)2023=o(nϵ) (\log n)^{2023} = o(n^\epsilon) for any ϵ>0 \epsilon > 0 .

Step 4: Verify and Summarize

  • Therefore, we can say that f(n) f(n) is bounded above by n12 n^{\frac{1}{2}} , n13 n^{\frac{1}{3}} , and so forth, since logarithmic growth is significantly slower than polynomial growth.
  • A suitable asymptotic upper bound could be O((logn)2024) O((\log n)^{2024}) as it captures the growth of f(n) f(n) without exceeding it for sufficiently large n n .

Final Answer

The correct asymptotic upper bound for f(n)=(logn)2023 f(n) = (\log n)^{2023} is: f(n)=O((logn)2024) f(n) = O((\log n)^{2024})

This problem has been solved

Similar Questions

Which of the given options provides the increasing order of complexity of functions f1, f2, f3 and f4:f1(n) = 2^nf2(n) = n^(3/2)f3(n) = nLognf4(n) = n^(Logn)

5. Arrange the functionsn , 1000 log n, n log n, 2n!, 2n, 3n, and n2/1,000,000 in a list sothat each function is big-O of the next function.

6. Give as good a big-O estimate as possible for each of these functions.a) (n2 + 8)(n + 1) b) (n log n + n2)(n3 + 2) c) (n! + 2n)(n3 + log(n2 + 1))

Consider the following recurrence relation for a function T(n):T(n) = 3T(n/2​) + nUse the recursion tree method to determine the time complexity of T(n)

f(n) = 2^(2n)Which of the following correctly represents the above function?Select one:O(2^n)Ω(2^n)Θ(2^n)None of these

1/1

Upgrade your grade with Knowee

Get personalized homework help. Review tough concepts in more detail, or go deeper into your topic by exploring other relevant questions.