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Write your theoretical analysis for the brute force case Write your theoretical analysis for the divide-and-conquer case

Write your theoretical analysis for the brute force case Write your theoretical analysis for the divide-and-conquer case

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Subject: Computer Science Design & Analysis of algorithms

Questions:

  1. Write your theoretical analysis for the brute force case
  2. Write your theoretical analysis for the divide-and-conquer case

Note: The algorithms of both techniques are both answered before but I need to know their theoretical analysis.

- Problem Statement During tough times like these, investment becomes more uncertain with more dangers. To solve it, we might try to train a model to decide when to buy or sell. Therefore, to provide it with correct data, we plan to design an algorithm that answers: • what is the perfect moment to buy and when to sell to maximize your profit? Assume you must buy Input: changes : array listing changes in the prices, where indices represent days; it has at least two values Output: i : index of the change before which we buy j: index of the change before which we sell maxProfit : the profit of this interval Example: Assume the below table contains the prices of a particular stock over days prices changes Day Value 50 - 1 63 13 2 70 7 3 40 -30 4 55 15 5 65 10 6 60 -5 7 72 12 8 79 7 9. 68 -11 10 74 6. Therefore, the output of maxProfit([13,7,-30,15,10, -5,12,7,-11,6]) should be (3, 7, 39) . This is because our maximum profit would be 39 when we buy the stock at day 4, index of 3, and sell after day 8, index of 7. Then, the total profit is 15+ 10 – 5+ 12+7= 39
Transcribed Image Text:- Problem Statement During tough times like these, investment becomes more uncertain with more dangers. To solve it, we might try to train a model to decide when to buy or sell. Therefore, to provide it with correct data, we plan to design an algorithm that answers: • what is the perfect moment to buy and when to sell to maximize your profit? Assume you must buy Input: changes : array listing changes in the prices, where indices represent days; it has at least two values Output: i : index of the change before which we buy j: index of the change before which we sell maxProfit : the profit of this interval Example: Assume the below table contains the prices of a particular stock over days prices changes Day Value 50 - 1 63 13 2 70 7 3 40 -30 4 55 15 5 65 10 6 60 -5 7 72 12 8 79 7 9. 68 -11 10 74 6. Therefore, the output of maxProfit([13,7,-30,15,10, -5,12,7,-11,6]) should be (3, 7, 39) . This is because our maximum profit would be 39 when we buy the stock at day 4, index of 3, and sell after day 8, index of 7. Then, the total profit is 15+ 10 – 5+ 12+7= 39
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