I'm really confused about the differences between big O, big Omega, and big Theta notation.
I understand that big O is the upper bound and big Omega is the lower bound, but what exactly does big Ө (theta) represent?
I have read that it means tight bound, but what does that mean?
It means that the algorithm is both big-O and big-Omega in the given function.
For example, if it is Ө(n)
, then there is some constant k
, such that your function (run-time, whatever), is larger than n*k
for sufficiently large n
, and some other constant K
such that your function is smaller than n*K
for sufficiently large n
.
In other words, for sufficiently large n
, it is sandwiched between two linear functions :
For k < K
and n
sufficiently large, n*k < f(n) < n*K