diff --git a/src/data/roadmaps/datastructures-and-algorithms/content/104-algorithmic-complexity/103-asymptotic-notation/102-big-omega.md b/src/data/roadmaps/datastructures-and-algorithms/content/104-algorithmic-complexity/103-asymptotic-notation/102-big-omega.md index d76cc353d..0b9d5343a 100644 --- a/src/data/roadmaps/datastructures-and-algorithms/content/104-algorithmic-complexity/103-asymptotic-notation/102-big-omega.md +++ b/src/data/roadmaps/datastructures-and-algorithms/content/104-algorithmic-complexity/103-asymptotic-notation/102-big-omega.md @@ -1,3 +1,3 @@ # Big-Ω Notation -The Big Omega (Ω) notation is used in computer science to describe an algorithm's lower bound. Essentially, it provides a worst-case analysis of an algorithm's efficiency, giving us a lower limit of the performance. If we say a function f(n) is Ω(g(n)), it means that from a certain point onwards (n0 for some constant n0), the value of g(n) is a lower bound on f(n). It implies that f(n) is at least as fast as g(n) past a certain threshold. This means that the algorithm won't perform more efficiently than the Ω time complexity suggests. \ No newline at end of file +The Big Omega (Ω) notation is used in computer science to describe an algorithm's lower bound. Essentially, it provides a best-case analysis of an algorithm's efficiency, giving us a lower limit of the performance. If we say a function f(n) is Ω(g(n)), it means that from a certain point onwards (n0 for some constant n0), the value of g(n) is a lower bound on f(n). It implies that f(n) is at least as fast as g(n) past a certain threshold. This means that the algorithm won't perform more efficiently than the Ω time complexity suggests.