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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Chapter 3, Problem 29SG
Program Plan Intro
E-book reader:
E-book reader is a mobile electronic device used for reading the digital e-books and periodicals. It is also termed as e-book device or e-reader. It is available is MAC and PC computer systems and android, iOS and Windows devices.
Program Plan Intro
Wearable device:
Wearable device is a small mobile computing device communicated by connected with Bluetooth. It is connected to smart phone using Bluetooth. It includes three types namely, tracker, smart watch and smart glass.
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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 3 Solutions
Discovering Computers ©2018: Digital Technology, Data, and Devices
Ch. 3 - Prob. 1SGCh. 3 - Prob. 2SGCh. 3 - Prob. 3SGCh. 3 - Prob. 4SGCh. 3 - Prob. 5SGCh. 3 - Prob. 6SGCh. 3 - Prob. 7SGCh. 3 - Prob. 8SGCh. 3 - Prob. 9SGCh. 3 - Prob. 10SG
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