From 611be3742a17597fe2f2b0ee3a56e512635ce735 Mon Sep 17 00:00:00 2001 From: Jidong Xiao Date: Tue, 19 Sep 2023 23:33:42 -0400 Subject: [PATCH] sup to sub --- lectures/07_order_notation_recursion/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lectures/07_order_notation_recursion/README.md b/lectures/07_order_notation_recursion/README.md index 58e2136..6e12c3b 100644 --- a/lectures/07_order_notation_recursion/README.md +++ b/lectures/07_order_notation_recursion/README.md @@ -47,7 +47,7 @@ Which company has the “best” algorithm? In this course we will focus on the intuition of order notation. This topic will be covered again, in more depth, in later computer science courses. -- Definition: Algorithm A is order f(n) — denoted O(f(n)) — if constants k and n0 exist such that A requires no more than k * f(n) time units (operations) to solve a problem of size n ≥ n0. +- Definition: Algorithm A is order f(n) — denoted O(f(n)) — if constants k and n0 exist such that A requires no more than k * f(n) time units (operations) to solve a problem of size n ≥ n0. - For example, algorithms requiring 3n + 2, 5n − 3, and 14 + 17n operations are all O(n). This is because we can select values for k and n0 such that the definition above holds. (What values?) Likewise, algorithms requiring n2/10 + 15n − 3 and 10000 + 35n2 are all O(n2).