Master Method: Bounding Recurrences using the Master Theorem, Assignments of Computer Science

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

Pre 2010

Uploaded on 03/28/2010

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cs141 Workshop: The Master Method
The Master Theorem:
Let
a and b be constants, let 1 1>
(
)
f
n be a function, and let Tn be defined
on the nonnegative integers by the recurrence:
()
(
)
(
)
(
)
/Tn aTnb f n=+
,
where we interpret n to mean either /b/nb
or /nb
. Then
(
)
Tn can be bounded
asymptotically as follows:
1. If
fn
()
(
logba
n
)
ε
for some constant 0
ε
>, then
(
)
(
)
logba
nTn .
2. If
()
(
log log
bak
)
f
nn nfor some constant , then 0k
(
)
()
log 1
log
bak
Tn n n
+
.
3. If
fn
()
(
logba
n
)
ε
+
=Ω for some constant 0
>, and if
(
)(
/n b cf n
)
af for some
constant c and all sufficiently large n, then 1<
(
)
(
)
(
)
fnTn .
Use the master method (where applicable) to solve the following recurrence
relations:
Assume that Tn is constant for
()
2n
.
1.
() ( )
3
2/2Tn Tn n=+
2.
() ( )
9/10Tn T n n=+
3.
()
(
)
2
16 / 4Tn Tn n=+
4.
() ( )
2
7/3Tn Tn n=+
5.
() ( )
2
7/2Tn Tn n=+
6.
() ( )
2/4Tn Tn n=+
7.
() ( )
1Tn Tn n=−+
8.
()
()
1Tn T n=+
9.
() ( )
3/2 lgTn Tn n n=+
10.
() ( )
3/35 /Tn Tn n=++2
11.
()
2/2 /lgTn n n+
12.
() ( )
11/Tn Tn n=−+
13.
() ( )
1lgTn Tn n=−+
14.
()
()
Tn nT n n=+
15.
() ( )
3/4Tn Tn n=+
16.
() ( )
2/2Tn Tn n=+
2
17.
() ( )
4/2Tn Tn n=+

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cs141 Workshop: The Master Method

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:

  1. If f n

log

b

a

n

− ε

= Ο for some constant ε > 0 , then

log

b

a

T n = Θ n.

  1. If

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

  1. If f n

log

b

a

n

  • ε

= Ω for some constant ε > 0 , and if

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