EBK DATA STRUCTURES AND ALGORITHMS IN C
4th Edition
ISBN: 9781285415017
Author: DROZDEK
Publisher: YUZU
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Chapter 2, Problem 12E
Program Plan Intro
Amortized Analysis:
Analyzing time complexity, amount of resource, time and memory space requirements for execution of an
- Aggregate Analysis - It determines upper bound “T(n)” on “n” operation sequence’s total cost, amortized cost would be
- Accounting Method - It determines each operation’s individual cost, which combines its execution time and running time influence of future operations.
- Potential Method - It determines each operation’s individual cost like accounting method, but operations are overcharged compensating for later undercharges.
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Assignment 2
this homework
Question 1: Consider the given table and determine
Source
Pi
a. The source code using Fano Coding technique.
b. Determine the average length of code.
c. Determine the entropy of the source.
d. Determine the efficiency of the code.
S1
0.3
S2
0.2
S3
0.2
S4
0.1
S5
0.1
S6
0.05
S7
0.05
Computer Science
(a) Let A = (Q,Σ,δ,q0,F) be a DFA.Formally describe a 2-tape TM with 3 states that accepts L(A).
(b) Let M = (Q, Σ, Γ, δ, q0, qa, qr) be a single-tape TM.Formally describe a 2-tape TM with 3 states that accepts L(M).
Running times of counting. Consider an n-bit counter that counts from 0 to 2" - 1. At each
step, its value is incremented. For example, when n = 5, the counter has the following values:
Step
0
1
2
3
4
⠀
30
31
(a)
Value # Bit-Flips
00000
00001
00010
00011
00100
11110
11111
1
2
1
3
2
1
The "Bit-Flips" column shows how many bits need to be flipped at that step. Note that to go from a count
of 0 to 1, we only need to flip the last bit. But when we increase the count from 1 to 2, we need to flip the
last two bits.
Argue why you need O(n2") bit-flips to count from 0 to 2" - 1.
Chapter 2 Solutions
EBK DATA STRUCTURES AND ALGORITHMS IN C
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