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- What is the difference between O, Ω, and Θ? - Stack Overflow
I am learning algorithm analysis I am having trouble understanding the difference between O, Ω, and Θ The way they're defined is as follows: f(n) = O(g(n)) means c · g(n) is an upper boun
- What is the difference between lower bound and tight bound?
Θ-notation (theta notation) is called tight-bound because it's more precise than O-notation and Ω-notation (omega notation) If I were lazy, I could say that binary search on a sorted array is O (n 2), O (n 3), and O (2 n), and I would be technically correct in every case That's because O-notation only specifies an upper bound, and binary search is bounded on the high side by all of those
- algorithm - Big-oh vs big-theta - Stack Overflow
Possible Duplicate: What is the difference between Θ(n) and O(n)? It seems to me like when people talk about algorithm complexity informally, they talk about big-oh But in formal situations, I oft
- Big Omega notation - what is f = Ω (g)? - Stack Overflow
I've been trying for the better part of an hour to find reference to the following: f = Ω(g) But I have had no luck at all I need to answer a question for an assignment and I can't find referenc
- sorting - comparison sort algorithms requires Ω (nlgn) comparisons in . . .
This was taken from the popular book called Intro to Algorithms The author states that any comparison sort algorithm requires Ω(nlgn) comparisons in the worst case Taking the bubble sort algorith
- What is the difference between Θ(n) and O(n)? - Stack Overflow
There's a simple way (a trick, I guess) to remember which notation means what All of the Big-O notations can be considered to have a bar When looking at a Ω, the bar is at the bottom, so it is an (asymptotic) lower bound When looking at a Θ, the bar is obviously in the middle So it is an (asymptotic) tight bound When handwriting O, you usually finish at the top, and draw a squiggle
- performance - what does O (N) mean - Stack Overflow
Possible Duplicate: What is Big O notation? Do you use it? Hi all, fairly basic scalability notation question I recently recieved a comment on a post that my python ordered-list implimentati
- math - Is 2^ (2n) = O (2^n) - Stack Overflow
First case is obviously true - you just multiply the constant C in by 2 Current answers to the second part of the question, look like a handwaving to me, so I will try to give a proper math explanation Let's assume that the second part is true, then from the definition of big-O, you have: which is clearly wrong, because there is no such constant that satisfy such inequality
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