obtain the exact solution to the recurrence n=2k (restricted solution). K Use this to obtain the complexity of T(n) when n=2k (restricted complexity) T(1) = 1/2 T(n) = T (L½1) 1 n(n+1) , ndo
obtain the exact solution to the recurrence n=2k (restricted solution). K Use this to obtain the complexity of T(n) when n=2k (restricted complexity) T(1) = 1/2 T(n) = T (L½1) 1 n(n+1) , ndo
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Question
![### Solving Recurrence Relations
**Objective**: Obtain the exact solution to the recurrence for \( n = 2^k \) (restricted solution). Use this to find the time complexity of \( T(n) \) when \( n = 2^k \) (restricted complexity).
#### Given Recurrence Relation
\[ T(1) = \frac{1}{2} \]
\[ T(n) = T\left(\left\lfloor \frac{n}{2} \right\rfloor \right) + \frac{1}{n(n+1)} \]
#### Conditions
- The recurrence relation must be solved for \( n \geq 0 \).
This problem involves solving a recurrence relation where the input size \( n \) reduces by half in each step, which is a common pattern in divide-and-conquer algorithms like merge sort or binary tree operations. The recurrence provides a base case for \( n = 1 \) and defines how \( T(n) \) is computed based on smaller subproblems.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F5c1f44d6-2912-49cf-894d-a588f3241dc5%2F3e586782-0865-48b8-b223-d9d7bfde7b1b%2Fduwogp6_processed.jpeg&w=3840&q=75)
Transcribed Image Text:### Solving Recurrence Relations
**Objective**: Obtain the exact solution to the recurrence for \( n = 2^k \) (restricted solution). Use this to find the time complexity of \( T(n) \) when \( n = 2^k \) (restricted complexity).
#### Given Recurrence Relation
\[ T(1) = \frac{1}{2} \]
\[ T(n) = T\left(\left\lfloor \frac{n}{2} \right\rfloor \right) + \frac{1}{n(n+1)} \]
#### Conditions
- The recurrence relation must be solved for \( n \geq 0 \).
This problem involves solving a recurrence relation where the input size \( n \) reduces by half in each step, which is a common pattern in divide-and-conquer algorithms like merge sort or binary tree operations. The recurrence provides a base case for \( n = 1 \) and defines how \( T(n) \) is computed based on smaller subproblems.
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Step 1
Given:
recurrence relation
Now,
to equation (1).
Now, replace the value in equation (1)
Now
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