Discovering Computers ©2018: Digital Technology, Data, and Devices
1st Edition
ISBN: 9781337285100
Author: Misty E. Vermaat, Susan L. Sebok, Steven M. Freund, Jennifer T. Campbell, Mark Frydenberg
Publisher: Cengage Learning
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Expert Solution & Answer
Chapter 2, Problem 20CT
Explanation of Solution
Difference between JPEG and PNG:
| JPEG | PNG |
| This stands for Joint photographic experts group | This stands for portable network groups. |
| The lossy compression | The lossless algorithm used in PNG keeps all the information. |
| In this case the images are made very small, but it degrades the quality very quickly... |
Expert Solution & Answer
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Students have asked these similar questions
Design a dynamic programming algorithm for the Longest Alternating Subsequence problem
described below:
Input: A sequence of n integers
Output: The length of the longest subsequence where the numbers alternate between being larger and
smaller than their predecessor
The algorithm must take O(n²) time. You must also write and explain the recurrence.
Example 1:
Input: [3, 5, 4, 1, 3, 6, 5, 7, 3, 4]
Output: 8 ([3, 5, 4, 6, 5, 7, 3, 4])
Example 2:
Input: [4,7,2,5,8, 3, 8, 0, 4, 7, 8]
Output: 8 ([4, 7, 2, 5, 3, 8, 0,4])
(Take your time with this for the subproblem for this one)
Design a dynamic programming algorithm for the Coin-change problem described below:
Input: An amount of money C and a set of n possible coin values with an unlimited supply of each
kind of coin.
Output: The smallest number of coins that add up to C exactly, or output that no such set exists.
The algorithm must take O(n C) time. You must also write and explain the recurrence.
Example 1:
Input: C24, Coin values = = [1, 5, 10, 25, 50]
Output: 6 (since 24 = 10+ 10+1+1 +1 + 1)
Example 2:
Input: C = 86, Coin values = [1, 5, 6, 23, 35, 46, 50]
Output: 2 (since 86 = 46+35+5)
Design a dynamic programming algorithm for the Longest Common Subsequence problem de-
scribed below
Input: Two strings x = x1x2 xm and y = Y1Y2... Yn
Output: The length of the longest subsequence that is common to both x and y.
.
The algorithm must take O(m n) time. You must also write and explain the recurrence.
(I want the largest k such that there are 1 ≤ i₁ < ... < ik ≤ m and 1 ≤ j₁ < ... < jk ≤ n such that
Xi₁ Xi2 Xik = Yj1Yj2 ··· Yjk)
Example 1:
Input: x = 'abcdefghijklmnopqrst' and y = 'ygrhnodsh ftw'
Output: 6 ('ghnost' is the longest common subsequence to both strings)
Example 2:
Input: x = 'ahshku' and y = ‘asu'
Output: 3 ('asu' is the longest common subsequence to both strings)
Chapter 2 Solutions
Discovering Computers ©2018: Digital Technology, Data, and Devices
Ch. 2 - Prob. 1SGCh. 2 - Prob. 2SGCh. 2 - Prob. 3SGCh. 2 - Prob. 4SGCh. 2 - Prob. 5SGCh. 2 - Prob. 6SGCh. 2 - Prob. 7SGCh. 2 - Prob. 8SGCh. 2 - Prob. 9SGCh. 2 - Prob. 10SG
Ch. 2 - Prob. 11SGCh. 2 - Prob. 12SGCh. 2 - Prob. 13SGCh. 2 - Prob. 14SGCh. 2 - Prob. 15SGCh. 2 - Prob. 16SGCh. 2 - Prob. 17SGCh. 2 - Prob. 18SGCh. 2 - Prob. 19SGCh. 2 - Prob. 20SGCh. 2 - Prob. 21SGCh. 2 - Prob. 22SGCh. 2 - Prob. 23SGCh. 2 - Prob. 24SGCh. 2 - Prob. 25SGCh. 2 - Prob. 26SGCh. 2 - Prob. 27SGCh. 2 - Prob. 28SGCh. 2 - Prob. 29SGCh. 2 - Prob. 30SGCh. 2 - Prob. 31SGCh. 2 - Prob. 32SGCh. 2 - Prob. 33SGCh. 2 - Prob. 34SGCh. 2 - Prob. 35SGCh. 2 - Prob. 36SGCh. 2 - Prob. 37SGCh. 2 - Prob. 38SGCh. 2 - Prob. 39SGCh. 2 - Prob. 40SGCh. 2 - Prob. 41SGCh. 2 - Prob. 42SGCh. 2 - Prob. 43SGCh. 2 - Prob. 44SGCh. 2 - Prob. 45SGCh. 2 - Prob. 46SGCh. 2 - Prob. 47SGCh. 2 - Prob. 48SGCh. 2 - Prob. 49SGCh. 2 - Prob. 1TFCh. 2 - Prob. 2TFCh. 2 - Prob. 3TFCh. 2 - Prob. 4TFCh. 2 - Prob. 5TFCh. 2 - Prob. 6TFCh. 2 - Prob. 7TFCh. 2 - Prob. 8TFCh. 2 - Prob. 9TFCh. 2 - Prob. 10TFCh. 2 - Prob. 11TFCh. 2 - Prob. 12TFCh. 2 - Prob. 1MCCh. 2 - Prob. 2MCCh. 2 - Prob. 3MCCh. 2 - Prob. 4MCCh. 2 - Prob. 5MCCh. 2 - Prob. 6MCCh. 2 - Prob. 7MCCh. 2 - Prob. 8MCCh. 2 - Prob. 1MCh. 2 - Prob. 2MCh. 2 - Prob. 3MCh. 2 - Prob. 4MCh. 2 - Prob. 5MCh. 2 - Prob. 6MCh. 2 - Prob. 7MCh. 2 - Prob. 8MCh. 2 - Prob. 9MCh. 2 - Prob. 10MCh. 2 - Prob. 2CTCh. 2 - Prob. 3CTCh. 2 - Prob. 4CTCh. 2 - Prob. 5CTCh. 2 - Prob. 6CTCh. 2 - Prob. 7CTCh. 2 - Prob. 8CTCh. 2 - Prob. 9CTCh. 2 - Prob. 10CTCh. 2 - Prob. 11CTCh. 2 - Prob. 12CTCh. 2 - Prob. 13CTCh. 2 - Prob. 14CTCh. 2 - Prob. 15CTCh. 2 - Prob. 16CTCh. 2 - Prob. 17CTCh. 2 - Prob. 18CTCh. 2 - Prob. 19CTCh. 2 - Prob. 20CTCh. 2 - Prob. 21CTCh. 2 - Prob. 22CTCh. 2 - Prob. 23CTCh. 2 - Prob. 24CTCh. 2 - Prob. 25CTCh. 2 - Prob. 26CTCh. 2 - Prob. 27CTCh. 2 - Prob. 1PSCh. 2 - Prob. 2PSCh. 2 - Prob. 3PSCh. 2 - Prob. 4PSCh. 2 - Prob. 5PSCh. 2 - Prob. 6PSCh. 2 - Prob. 7PSCh. 2 - Prob. 8PSCh. 2 - Prob. 9PSCh. 2 - Prob. 10PSCh. 2 - Prob. 11PSCh. 2 - Prob. 1.1ECh. 2 - Prob. 1.2ECh. 2 - Prob. 1.3ECh. 2 - Prob. 2.1ECh. 2 - Prob. 2.2ECh. 2 - Prob. 2.3ECh. 2 - Prob. 3.1ECh. 2 - Prob. 3.2ECh. 2 - Prob. 3.3ECh. 2 - Prob. 4.1ECh. 2 - Prob. 4.2ECh. 2 - Prob. 4.3ECh. 2 - Prob. 5.1ECh. 2 - Prob. 5.2ECh. 2 - Prob. 5.3ECh. 2 - Prob. 1IRCh. 2 - Prob. 2IRCh. 2 - Prob. 3IRCh. 2 - Prob. 4IRCh. 2 - Prob. 1CTQCh. 2 - Prob. 2CTQCh. 2 - Prob. 3CTQ
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