## ← Other sets of Functions - Intro to Algorithms

• 2 フォロワーs
• 12 Lines

### 埋め込みコードを取得する x Embed video Use the following code to embed this video. See our usage guide for more details on embedding. Paste this in your document somewhere (closest to the closing body tag is preferable): ```<script type="text/javascript" src='https://amara.org/embedder-iframe'></script> ``` Paste this inside your HTML body, where you want to include the widget: ```<div class="amara-embed" data-url="http://www.youtube.com/watch?v=3OKOwtOOzrM" data-team="udacity"></div> ``` 3言語

Showing Revision 2 created 05/24/2016 by Udacity Robot.

1. Big Θ is just one of a bunch of different functions that we can define,
2. and there's a set that essentially corresponds to all the different ways you might
3. want to compare a function.
4. If f(n) is in little o(g(n)), that's kind of like saying f(n) is strictly less than g(n).
5. It grows less slowly asymptotically.
6. F(n) is in O(g(n))--there's our friend O--that's really like saying f(n) ≤ g(n).
7. It might grow as fast as g(n), but it might be small.
8. Θ is the one we just looked at, which kind of like equality--they grow roughly at the same rate.
9. Ω--f(n) is in Ω(g(n)) means that it is an upper bound.
10. F(n) is bigger than or equal to g(n).
11. G(n) is a lower bound on f(n).
12. The ω, analogously, is kind of like strictly greater than.