I know that the running time of merge sort 开发者_StackOverflow中文版is O(n*lg(n)) and that merge sort is a comparision sort, which also means that it takes Ω(n logn) in the worst case to sort a list
I\'m trying to figure out whether f(n)=n^(logb(n)) is in Theta(n^k) and therefore grows polynomial or in Theta(k^n) and therefore grows exponentially.
I\'m going to preface this with the fact that I am not completely knowledgeable on Big O Notation, so maybe my thinking about this is off.
The well known bogosort algorithm simply shuffles a deck until it is in order while not inOrder(deck) do
I am going over the Big-Oh notation, and I have a problem understanding the solution to this question:
I have the f开发者_运维技巧ollowing question: Is the following statement true or false? All logs to base 2
Let A[1..n] be an array of real numbers. Design an algorithm to perform any sequence of the following operations:
I have received the assignment to prove 1/O(n) = Ω(n) However, this would mean that n element of O(n) => 1/n element of Ω(n) which is clearly wrong.开发者_StackOverflow中文版
This algorithm look开发者_Go百科s through a string and tries to find another string. The logic is simple, I guess. Though, I need help finding it\'s complexity.
I have the following question: Solve the recurrence relation simplifying the answer using Big \'O\' notation:
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