O-notation (Upper Bound - Worst Case) 14 O(g(n)) = {f(n): there exist positive constants c and no such that 0 ≤ f(n) ≤ cg(n) for all n ≥ no} . cg(n) no f(n) n f(n) = 0(g(n)) g(n) is an asymptotic upper bound for f(n). If f(n) = O(g(n)), we write f(n) = 0(g(n)) Example 2n² = 0(³), with c = 1 and no = 2. Examples of functions in 0(²): n² n² +n n²+1000m 1000m²+1000m Also, Examples (T/F): 2n=0(1)? n/1000 2n=0(lgn)? n²/lg lg lgn 1.99999 2n=0(n)? 2n=0(²)? 2n=0(³)?
O-notation (Upper Bound - Worst Case) 14 O(g(n)) = {f(n): there exist positive constants c and no such that 0 ≤ f(n) ≤ cg(n) for all n ≥ no} . cg(n) no f(n) n f(n) = 0(g(n)) g(n) is an asymptotic upper bound for f(n). If f(n) = O(g(n)), we write f(n) = 0(g(n)) Example 2n² = 0(³), with c = 1 and no = 2. Examples of functions in 0(²): n² n² +n n²+1000m 1000m²+1000m Also, Examples (T/F): 2n=0(1)? n/1000 2n=0(lgn)? n²/lg lg lgn 1.99999 2n=0(n)? 2n=0(²)? 2n=0(³)?
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
In this example, which of the Big O, is true and false?
![**O-notation (Upper Bound – Worst Case)**
**Definition:**
\[ O(g(n)) = \{ f(n) : \text{there exist positive constants } c \text{ and } n_0 \text{ such that } 0 \leq f(n) \leq c g(n) \text{ for all } n \geq n_0 \} \]
**Diagram Explanation:**
- The graph illustrates two functions: \( f(n) \) and \( c g(n) \).
- The curve \( f(n) \) is shown as a blue line, which increases and intersects with the \( c g(n) \) line, depicted as a black line.
- The diagram emphasizes that beyond a certain value \( n_0 \), \( f(n) \) stays below or equal to \( c g(n) \).
- \( n_0 \) is the threshold from which \( f(n) = O(g(n)) \) holds true.
**Explanation:**
- \( g(n) \) is an asymptotic upper bound for \( f(n) \).
- If \( f(n) \in O(g(n)) \), we write \( f(n) = O(g(n)) \).
**Example (from the red box):**
- \( 2n^2 = O(n^3) \), with \( c = 1 \) and \( n_0 = 2 \).
**Examples of functions in \( O(n^2) \):**
- \( n^2 \)
- \( n^2 + n \)
- \( n^2 + 1000n \)
- \( 1000n^2 + 1000n \)
**Also:**
- \( n \)
- \( n/1000 \)
- \( n^{1.99999} \)
- \( n^2 / \lg \lg n \)
**Examples (True/False):**
- \( 2n = O(1)? \)
- \( 2n = O(\log n)? \)
- \( 2n = O(n)? \)
- \( 2n = O(n^2)? \)
- \( 2n = O(n^3)? \)](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F346b36e0-a4d8-47d7-8bd1-1ad776cb1cf3%2F1a915778-c54e-42e5-b532-88445c616f9e%2Fsmhyygb_processed.png&w=3840&q=75)
Transcribed Image Text:**O-notation (Upper Bound – Worst Case)**
**Definition:**
\[ O(g(n)) = \{ f(n) : \text{there exist positive constants } c \text{ and } n_0 \text{ such that } 0 \leq f(n) \leq c g(n) \text{ for all } n \geq n_0 \} \]
**Diagram Explanation:**
- The graph illustrates two functions: \( f(n) \) and \( c g(n) \).
- The curve \( f(n) \) is shown as a blue line, which increases and intersects with the \( c g(n) \) line, depicted as a black line.
- The diagram emphasizes that beyond a certain value \( n_0 \), \( f(n) \) stays below or equal to \( c g(n) \).
- \( n_0 \) is the threshold from which \( f(n) = O(g(n)) \) holds true.
**Explanation:**
- \( g(n) \) is an asymptotic upper bound for \( f(n) \).
- If \( f(n) \in O(g(n)) \), we write \( f(n) = O(g(n)) \).
**Example (from the red box):**
- \( 2n^2 = O(n^3) \), with \( c = 1 \) and \( n_0 = 2 \).
**Examples of functions in \( O(n^2) \):**
- \( n^2 \)
- \( n^2 + n \)
- \( n^2 + 1000n \)
- \( 1000n^2 + 1000n \)
**Also:**
- \( n \)
- \( n/1000 \)
- \( n^{1.99999} \)
- \( n^2 / \lg \lg n \)
**Examples (True/False):**
- \( 2n = O(1)? \)
- \( 2n = O(\log n)? \)
- \( 2n = O(n)? \)
- \( 2n = O(n^2)? \)
- \( 2n = O(n^3)? \)
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