
Study with the several resources on Docsity
Earn points by helping other students or get them with a premium plan
Prepare for your exams
Study with the several resources on Docsity
Earn points to download
Earn points by helping other students or get them with a premium plan
An explanation of the master method, a technique used to analyze the asymptotic behavior of recurrence relations. The master theorem is presented, along with examples of how to apply it to various recurrences. Students of computer science, particularly those studying algorithms and data structures, will find this document useful for understanding the analysis of recurrences.
Typology: Assignments
1 / 1
This page cannot be seen from the preview
Don't miss anything!

The Master Theorem:
Let a ≥ 1 and b > 1 be constants, let
f n be a function, and let T n be defined
on the nonnegative integers by the recurrence:
T n = aT n b / + f n ,
where we interpret n / b to mean either n b /
or n b /
. Then
T n can be bounded
asymptotically as follows:
log
b
a
n
− ε
log
b
a
T n = Θ n.
log
log
b
a k
f n = Θ n n for some constant k ≥ 0 , then
log 1
log
b
a k
T n n n
log
b
a
n
n b / ≤ cf n
af for some
constant c < 1 and all sufficiently large n , then
T n = Θ f n.
Use the master method (where applicable) to solve the following recurrence
relations:
Assume that T n is constant for
n ≤ 2.
3
T n = 2 T n / 2 + n
T n = T 9 n /10 + n
2
T n = 16 T n / 4 + n
2
T n = 7 T n / 3 + n
2
T n = 7 T n / 2 + n
T n = 2 T n / 4 + n
T n = T n − 1 + n
T n = T n + 1
T n = 3 T n / 2 + n lg n
T n = 3 T n / 3 + 5 + n / 2
2 T n / 2 + n / lg n
T n = T n − 1 +1/ n
T n = T n − 1 +lg n
T n = nT n + n
T n = 3 T n / 4 + n
T n = 2 T n / 2 + n
2
T n = 4 T n / 2 + n