1252 lines
40 KiB
Markdown
1252 lines
40 KiB
Markdown
---
|
|
title: Order of Growth
|
|
TARGET DECK: Obsidian::STEM
|
|
FILE TAGS: algorithm::complexity
|
|
tags:
|
|
- algorithm
|
|
- complexity
|
|
---
|
|
|
|
## Overview
|
|
|
|
The **running time** of an algorithm is usually considered as a function of its **input size**. How input size is measured depends on the problem at hand. For instance, [[algorithms/sorting/index|sorting]] algorithms have an input size corresponding to the number of elements to sort.
|
|
|
|
%%ANKI
|
|
Basic
|
|
How is the running time of a program measured as a function?
|
|
Back: As a function of its input size.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1707334419352-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
How do you determine the input size used to measure an algorithm's running time?
|
|
Back: This depends entirely on the specific problem/algorithm.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1707334419356-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What *concrete* measure is typically used to measure running time?
|
|
Back: The number of primitive operations executed.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1707334419359-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What *abstract* measure is typically used to measure running time?
|
|
Back: It's order of growth.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1707344177499-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Why does Cormen et al. state the scope of average-case analysis is limited?
|
|
Back: What constitutes an "average" input isn't always clear.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1707334419363-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What about running time are algorithm designers mostly interested in?
|
|
Back: It's order of growth.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1707344177503-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
How does order of growth relate to running time?
|
|
Back: Order of growth measures how quickly running time grows with respect to input size.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1707344177506-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Why are lower-ordered terms ignored when determining order of growth?
|
|
Back: They become less significant as input size grows.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1707344177510-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Why are leading coefficients ignored when determining order of growth?
|
|
Back: They become less significant as input size grows.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1707344177513-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Polynomials describing order of growth usually have what two parts ignored?
|
|
Back: Coefficients and lower-ordered terms.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1707344177515-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
How do we simplify $\Theta(an^2 + bn + c)$?
|
|
Back: As $\Theta(n^2)$.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221765-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Explain why asymptotic notation is useful for *both* running times and space usage.
|
|
Back: Asymptotic notation represents functions in a general sense.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221769-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
*Which* running time are algorithm designers typically concerned with?
|
|
Back: Worst-case running time.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221774-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
In asymptotic notation, how is constant space usage denoted?
|
|
Back: Space usage is $O(1)$.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221778-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
How could we replace equality $f(n) = \Theta(g(n))$ to be less "abusive"?
|
|
Back: Replace $=$ with $\in$.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221783-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
How is equality abused in $f(n) = \Theta(g(n))$?
|
|
Back: Here $=$ actually refers to set membership.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221788-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
How could we replace $1$ in $\Theta(1)$ to be less "abusive"?
|
|
Back: Replace $1$ with $n^0$.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221793-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
*Why* does Cormen et al. consider $\Theta(1)$ to be a minor abuse?
|
|
Back: This expression does not indicate what variable is tending to infinity.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221797-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
What does it mean for function $f(n)$ to be asymptotically nonnegative?
|
|
Back: $f(n) \geq 0$ whenever $n$ is sufficiently large.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What does it mean for function $f(n)$ to be asymptotically positive?
|
|
Back: $f(n) > 0$ whenever $n$ is sufficiently large.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221871-->
|
|
END%%
|
|
|
|
When encountering equations with asymptotic notation on both sides of the equality, we interpret the equation using the following rule:
|
|
|
|
> No matter how the anonymous functions are chosen on the left of the equal sign, there is a way to choose the anonymous functions on the right of the equal sign to make the equation valid.
|
|
|
|
For example, $2n^2 + \Theta(n) = \Theta(n^2)$ states that for all $f(n) \in \Theta(n)$, there exists some $g(n) \in \Theta(n^2)$ such that $2n^2 + f(n) = g(n)$.
|
|
|
|
%%ANKI
|
|
Basic
|
|
Asymptotic notation on the RHS of an equation is a stand in for what?
|
|
Back: *Some* function in the set that satisfies the equation.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002305-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Asymptotic notation on the LHS of an equation is a stand in for what?
|
|
Back: *Any* function in the set.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002309-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Cloze
|
|
In equations containing asymptotic notation, {1:LHS} is to {1:$\forall$} whereas {2:RHS} is to {2:$\exists$}.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002313-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
How is $2n^2 + \Theta(n) = \Theta(n^2)$ written in propositional logic?
|
|
Back: $\forall f(n) \in \Theta(n), \exists g(n) \in \Theta(n^2), 2n^2 + f(n) = g(n)$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002316-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
*Why* is $\sum_{i=1}^n O(i) \neq O(1) + O(2) + \cdots + O(n)$?
|
|
Back: The number of anonymous functions is equal to the number of times the asymptotic notation appears.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002319-->
|
|
END%%
|
|
|
|
## $\Theta$-notation
|
|
|
|
![[theta-notation.png]]
|
|
|
|
$\Theta$-notation refers to a strict lower- and upper-bound. It is defined as set $$\Theta(g(n)) = \{ f(n) \mid \exists c_1, c_2, n_0 > 0, \forall n \geq n_0, 0 \leq c_1g(x) \leq f(n) \leq c_2g(n) \}$$
|
|
|
|
%%ANKI
|
|
Basic
|
|
What kind of mathematical object is $\Theta(g(n))$?
|
|
Back: A set.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221801-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Using typical identifiers found in $\Theta(g(n))$, what values do $c_1$, $c_2$, and $n_0$ take on?
|
|
Back: Positive constants.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221806-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What names are usually given to the existentially quantified identifers in $\Theta(g(n))$'s definition?
|
|
Back: $c_1$, $c_2$, and $n_0$.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221811-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What name is usually given to the universally quantified identifer in $\Theta(g(n))$'s definition?
|
|
Back: $n$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221815-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Cloze
|
|
Using typical identifiers, $f(n) = \Theta(g(n))$ satisfies {$0$} $\leq$ {$c_1g(n)$} $\leq$ {$f(n)$} $\leq$ {$c_2g(n)$}.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221818-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Using typical identifiers, what is the lower bound of $c_1g(n)$ in $\Theta(g(n))$?
|
|
Back: $0$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221822-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Using typical identifiers, what is the upper bound of $c_1g(n)$ in the definition of $\Theta(g(n))$?
|
|
Back: $f(n)$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221826-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Using typical identifiers, what is the lower bound of $f(n)$ in the definition of $\Theta(g(n))$?
|
|
Back: $c_1g(n)$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221830-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Using typical identifiers, what is the upper bound of $f(n)$ in the definition of $\Theta(g(n))$?
|
|
Back: $c_2g(n)$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221834-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Using typical identifiers, what is the lower bound of $c_2g(n)$ in $\Theta(g(n))$?
|
|
Back: $f(n)$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221839-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Using typical identifiers, what is the upper bound of $c_2g(n)$ in $\Theta(g(n))$?
|
|
Back: N/A
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221844-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Cloze
|
|
Given $f(n) = \Theta(g(n))$, we say {1:$g(n)$} is an asymptotic {2:tight} bound for {1:$f(n)$}.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221851-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Which notation corresponds to asymptotic tight bounds?
|
|
Back: $\Theta$-notation.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221857-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Every member of $\Theta(g(n))$ is expected to be asymptotically what?
|
|
Back: Nonnegative.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221864-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What condition must $g(n)$ satisfy such that $\Theta(g(n))$ is nonempty?
|
|
Back: $g(n)$ must be asymptotically nonnegative.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221876-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What does $\Theta(-n)$ evaluate to?
|
|
Back: $\varnothing$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221881-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
*Why* is it $\Theta(-n) = \varnothing$?
|
|
Back: Because $-n$ is not asymptotically nonnegative.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221886-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
How is $\Theta(g(n))$ defined?
|
|
Back: $\{ \exists c_1, c_2, n_0 > 0, \forall n \geq n_0, 0 \leq c_1g(n) \leq f(n) \leq c_2g(n) \}$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221892-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Using the typical identifiers, what values of $n$ are in the matrix of $\Theta(g(n))$'s definition?
|
|
Back: $n \geq n_0$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221898-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Which asymptotic notation is this image demonstrating?
|
|
![[theta-notation.png]]
|
|
Back: $\Theta$-notation
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221904-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
For $n < n_0$, what values does the $y$-axis take on?
|
|
![[theta-notation.png]]
|
|
Back: Indeterminate.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1708974221909-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
For $n \geq n_0$, what values does the $y$-axis take on?
|
|
![[theta-notation.png]]
|
|
Back: Nonnegative values.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709053894064-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What is the transitive property of $\Theta$-notation?
|
|
Back: $f(n) = \Theta(g(n))$ and $g(n) = \Theta(h(n))$ implies $f(n) = \Theta(h(n))$.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223294-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What is the reflexive property of $\Theta$-notation?
|
|
Back: $f(n) = \Theta(f(n))$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223298-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What condition must $f(n)$ satisfy for equality $f(n) = \Theta(f(n))$ to hold?
|
|
Back: $f(n)$ must be nonnegatively asymptotic.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223303-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
*Why* must $f(n)$ be nonnegatively asymptotic for $f(n) = \Theta(f(n))$ to hold?
|
|
Back: Otherwise $\Theta(f(n))$ is the empty set.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223309-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What is the symmetric property of $\Theta$-notation?
|
|
Back: $f(n) = \Theta(g(n))$ iff $g(n) = \Theta(f(n))$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223316-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What is the transpose symmetric property of $\Theta$-notation?
|
|
Back: N/A
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223322-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
$\Theta$-notation is likened to what comparison operator of real numbers?
|
|
Back: $=$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223329-->
|
|
END%%
|
|
|
|
## $O$-notation
|
|
|
|
![[big-o-notation.png]]
|
|
|
|
$O$-notation refers to a strict upper-bound. It is defined as set $$O(g(n)) = \{ f(n) \mid \exists c, n_0 > 0, \forall n \geq n_0, 0 \leq f(n) \leq cg(n) \}$$
|
|
|
|
%%ANKI
|
|
Basic
|
|
What kind of mathematical object is $O(g(n))$?
|
|
Back: A set.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709053894066-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Using typical identifiers found in $O(g(n))$, what values do $c$ and $n_0$ take on?
|
|
Back: Positive constants.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709053894068-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What names are usually given to the existentially quantified identifers in $O(g(n))$'s definition?
|
|
Back: $c$ and $n_0$.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709053894070-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What name is usually given to the universally quantified identifer in $O(g(n))$'s definition?
|
|
Back: $n$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709053894072-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Cloze
|
|
Using typical identifiers, $f(n) = O(g(n))$ satisfies {$0$} $\leq$ {$f(n)$} $\leq$ {$cg(n)$}.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709053894074-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Using typical identifiers, what is the lower bound of $cg(n)$ in $O(g(n))$?
|
|
Back: $f(n)$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709053894076-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Using typical identifiers, what is the upper bound of $cg(n)$ in $O(g(n))$?
|
|
Back: N/A
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709053894078-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Using typical identifiers, what is the lower bound of $f(n)$ in $O(g(n))$?
|
|
Back: $0$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709053894080-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Using typical identifiers, what is the upper bound of $f(n)$ in $O(g(n))$?
|
|
Back: $cg(n)$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709750359817-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Cloze
|
|
Given $f(n) = O(g(n))$, we say {1:$g(n)$} is an asymptotic {2:upper} bound for {1:$f(n)$}.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709053894084-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Which notation corresponds to (potentially tight) asymptotic upper bounds?
|
|
Back: $O$-notation.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709053894088-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Every member of $O(g(n))$ is expected to be asymptotically what?
|
|
Back: Nonnegative.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709053894091-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What condition must $g(n)$ satisfy such that $O(g(n))$ is nonempty?
|
|
Back: $g(n)$ must be asymptotically nonnegative.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709053894093-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
How is $O(g(n))$ defined?
|
|
Back: $\{ \exists c, n_0 > 0, \forall n \geq n_0, 0 \leq f(n) \leq cg(n) \}$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709053894096-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Which asymptotic notation is this image demonstrating?
|
|
![[big-o-notation.png]]
|
|
Back: $O$-notation
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709053894098-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
When is it guaranteed $y$-values are nonnegative in the following?
|
|
![[big-o-notation.png]]
|
|
Back: When $n \geq n_0$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709053894100-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
In set-theoretic notation, what does it mean for $\Theta$-notation to be stronger than $O$-notation?
|
|
Back: $\Theta(g(n)) \subseteq O(g(n))$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709053894101-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What notation corresponds to worst-case running times?
|
|
Back: $O$-notation
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709053894103-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Why does Cormen et al. say "insertion sort's running time is $O(n^2)$" is an abuse of notation?
|
|
Back: Because technically its running time depends on the particular input of size $n$.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709053894105-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What is the transitive property of $O$-notation?
|
|
Back: $f(n) = O(g(n))$ and $g(n) = O(h(n))$ implies $f(n) = O(h(n))$.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223338-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What is the reflexive property of $O$-notation?
|
|
Back: $f(n) = O(f(n))$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223346-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What condition must $f(n)$ satisfy for equality $f(n) = O(f(n))$ to hold?
|
|
Back: $f(n)$ must be nonnegatively asymptotic.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223352-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
*Why* must $f(n)$ be nonnegatively asymptotic for $f(n) = O(f(n))$ to hold?
|
|
Back: Otherwise $O(f(n))$ is the empty set.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223358-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What is the symmetric property of $O$-notation?
|
|
Back: N/A
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223365-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What is the transpose symmetric property of $O$-notation?
|
|
Back: $f(n) = O(g(n))$ iff $g(n) = \Omega(f(n))$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223372-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
$O$-notation is likened to what comparison operator of real numbers?
|
|
Back: $\leq$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223381-->
|
|
END%%
|
|
|
|
## $o$-notation
|
|
|
|
$o$-notation refers to an upper bound that is not asymptotically tight. It is defined as set $$o(g(n)) = \{ f(n) \mid \forall c > 0, \exists n_0 > 0, \forall n \geq n_0, 0 \leq f(n) < cg(n) \}$$
|
|
|
|
%%ANKI
|
|
Basic
|
|
What kind of mathematical object is $o(g(n))$?
|
|
Back: A set.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002323-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Using typical identifiers found in $o(g(n))$, what values do $c$ and $n_0$ take on?
|
|
Back: Positive constants.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002325-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What names are usually given to the existentially quantified identifers in $o(g(n))$'s definition?
|
|
Back: $n_0$.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002328-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What names are usually given to the universally quantified identifers in $o(g(n))$'s definition?
|
|
Back: $c$ and $n$.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002331-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Cloze
|
|
Using typical identifiers, $f(n) = o(g(n))$ satisfies {$0$} $\leq$ {$f(n)$} $<$ {$cg(n)$}.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002334-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
How does $o$-notation compare to $O$-notation?
|
|
Back: The former denotes an upper bound that is not asymptotically tight.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002337-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
How is $o(g(n))$ pronounced?
|
|
Back: As "little-oh of $g$ of $n$".
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002340-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
How can $f(n) = o(g(n))$ be expressed as a limit?
|
|
Back: $$\lim_{n \to \infty} \frac{f(n)}{g(n)} = 0$$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002344-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Which notation corresponds to asymptotic upper bounds that are not tight?
|
|
Back: $o$-notation.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002347-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Every member of $o(g(n))$ is expected to be asymptotically what?
|
|
Back: Nonnegative.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002350-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
How is $o(g(n))$ defined?
|
|
Back: $\{ \forall c > 0, \exists n_0 > 0, \forall n \geq n_0, 0 \leq f(n) < cg(n) \}$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002353-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Cloze
|
|
In $O(g(n))$, bound {1:$0 \leq f(n) \leq cg(n)$} holds for {1:some $c > 0$}. In $o(g(n))$, {2:$0 \leq f(n) < cg(n)$} holds for {2:all $c > 0$}.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002359-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Is $O$-notation considered stronger or weaker than $o$-notation?
|
|
Back: Weaker.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002364-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What condition must $g(n)$ satisfy such that $o(g(n))$ is nonempty?
|
|
Back: $g(n)$ must be asymptotically positive.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709750359822-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What is the transitive property of $o$-notation?
|
|
Back: $f(n) = o(g(n))$ and $g(n) = o(h(n))$ implies $f(n) = o(h(n))$.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223391-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What is the reflexive property of $o$-notation?
|
|
Back: N/A
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223399-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
*Why* is there no reflexive property of $o$-notation?
|
|
Back: A function cannot be asymptotically smaller than itself.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223407-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What is the symmetric property of $o$-notation?
|
|
Back: N/A
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223417-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What is the transpose symmetric property of $o$-notation?
|
|
Back: $f(n) = o(g(n))$ iff $g(n) = \omega(f(n))$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223426-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
$o$-notation is likened to what comparison operator of real numbers?
|
|
Back: $<$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223435-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Cloze
|
|
{1:$\Omega$}-notation is to {2:$\geq$} whereas {2:$o$}-notation is to {1:$<$}.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223442-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
How do we set theoretically say $f(n)$ is asymptotically smaller than $g(n)$?
|
|
Back: $f(n) = o(g(n))$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223449-->
|
|
END%%
|
|
|
|
## $\Omega$-notation
|
|
|
|
![[big-omega-notation.png]]
|
|
|
|
$\Omega$-notation refers to a strict lower-bound. It is defined as set $$\Omega(g(n)) = \{ f(n) \mid \exists c, n_0 > 0, \forall n \geq n_0, 0 \leq cg(n) \leq f(n) \}$$
|
|
|
|
%%ANKI
|
|
Basic
|
|
What kind of mathematical object is $\Omega(g(n))$?
|
|
Back: A set.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709055157375-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Using typical identifiers found in $\Omega(g(n))$, what values do $c$ and $n_0$ take on?
|
|
Back: Positive constants.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709055157377-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What names are usually given to the existentially quantified identifers in $\Omega(g(n))$'s definition?
|
|
Back: $c$ and $n_0$.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709055157379-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What name is usually given to the universally quantified identifer in $\Omega(g(n))$'s definition?
|
|
Back: $n$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709055157381-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Cloze
|
|
Using typical identifiers, $f(n) = \Omega(g(n))$ satisfies {$0$} $\leq$ {$cg(n)$} $\leq$ {$f(n)$}.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709055157383-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Using typical identifiers, what is the lower bound of $cg(n)$ in $\Omega(g(n))$?
|
|
Back: $0$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709055157384-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Using typical identifiers, what is the upper bound of $cg(n)$ in $\Omega(g(n))$?
|
|
Back: $f(n)$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709055157386-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Using typical identifiers, what is the lower bound of $f(n)$ in $\Omega(g(n))$?
|
|
Back: $cg(n)$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709055157388-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Using typical identifiers, what is the upper bound of $f(n)$ in $\Omega(g(n))$?
|
|
Back: N/A
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709055157390-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Cloze
|
|
Given $f(n) = \Omega(g(n))$, we say {1:$g(n)$} is an asymptotic {2:lower} bound for {1:$f(n)$}.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709055157392-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Which notation corresponds to (potentially tight) asymptotic lower bounds?
|
|
Back: $\Omega$-notation.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709055157393-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Every member of $\Omega(g(n))$ is expected to be asymptotically what?
|
|
Back: Nonnegative.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709055157394-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What condition must $g(n)$ satisfy such that $\Omega(g(n))$ is nonempty?
|
|
Back: $g(n)$ must be asymptotically nonnegative.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709055157396-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
How is $\Omega(g(n))$ defined?
|
|
Back: $\{ \exists c, n_0 > 0, \forall n \geq n_0, 0 \leq cg(n) \leq f(n) \}$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709055157397-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Which asymptotic notation is this image demonstrating?
|
|
![[big-omega-notation.png]]
|
|
Back: $\Omega$-notation
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709055157399-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
In set-theoretic notation, what does it mean for $\Theta$-notation to be stronger than $\Omega$-notation?
|
|
Back: $\Theta(g(n)) \subseteq \Omega(g(n))$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709055157401-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What notation corresponds to best-case running times?
|
|
Back: $\Omega$-notation
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709055157402-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Cloze
|
|
{1:$O$}-notation is to asymptotic {2:upper}-bounds whereas {2:$\Omega$}-notation is to asymptotic {1:lower}-bounds.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709055157404-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What theorem relates $\Theta(g(n))$, $O(g(n))$, and $\Omega(g(n))$?
|
|
Back: $f(n) = \Theta(g(n))$ if and only if $f(n) \in O(g(n))$ and $f(n) \in \Omega(g(n))$.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709055157406-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What is the transitive property of $\Omega$-notation?
|
|
Back: $f(n) = \Omega(g(n))$ and $g(n) = \Omega(h(n))$ implies $f(n) = \Omega(h(n))$.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223456-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What is the reflexive property of $\Omega$-notation?
|
|
Back: $f(n) = \Omega(f(n))$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223462-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What condition must $f(n)$ satisfy for equality $f(n) = \Omega(f(n))$ to hold?
|
|
Back: $f(n)$ must be nonnegatively asymptotic.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223468-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
*Why* must $f(n)$ be nonnegatively asymptotic for $f(n) = \Omega(f(n))$ to hold?
|
|
Back: Otherwise $\Omega(f(n))$ is the empty set.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223477-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What is the symmetric property of $\Omega$-notation?
|
|
Back: N/A
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223486-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What is the transpose symmetric property of $\Omega$-notation?
|
|
Back: $f(n) = \Omega(g(n))$ iff $g(n) = O(f(n))$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223496-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
$\Omega$-notation is likened to what comparison operator of real numbers?
|
|
Back: $\geq$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223503-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Cloze
|
|
{1:$\Theta$}-notation is to {2:$=$} whereas {2:$\Omega$}-notation is to {1:$\geq$}.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223511-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Cloze
|
|
{1:$O$}-notation is to {2:$\leq$} whereas {2:$\Omega$}-notation is to {1:$\geq$}.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223522-->
|
|
END%%
|
|
|
|
## $\omega$-notation
|
|
|
|
$\omega$-notation refers to a lower bound that is not asymptotically tight. It is defined as set $$\omega(g(n)) = \{ f(n) \mid \forall c > 0, \exists n_0 > 0, \forall n \geq n_0, 0 \leq cg(n) < f(n) \}$$
|
|
|
|
%%ANKI
|
|
Basic
|
|
What kind of mathematical object is $\omega(g(n))$?
|
|
Back: A set.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002369-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Using typical identifiers found in $\omega(g(n))$, what values do $c$ and $n_0$ take on?
|
|
Back: Positive constants.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002374-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What names are usually given to the existentially quantified identifers in $\omega(g(n))$'s definition?
|
|
Back: $n_0$.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002380-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What names are usually given to the universally quantified identifers in $\omega(g(n))$'s definition?
|
|
Back: $c$ and $n$.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002385-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Cloze
|
|
Using typical identifiers, $f(n) = \omega(g(n))$ satisfies {$0$} $\leq$ {$cg(n)$} $<$ {$f(n)$}.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002390-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
How does $\omega$-notation compare to $\Omega$-notation?
|
|
Back: The former denotes a lower bound that is not asymptotically tight.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002395-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
How is $\omega(g(n))$ pronounced?
|
|
Back: As "little-omega of $g$ of $n$".
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002398-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
How can $f(n) = \omega(g(n))$ be expressed as a limit?
|
|
Back: $$\lim_{n \to \infty} \frac{f(n)}{g(n)} = \infty$$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002402-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Which notation corresponds to asymptotic lower bounds that are not tight?
|
|
Back: $\omega$-notation.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002406-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Every member of $\omega(g(n))$ is expected to be asymptotically what?
|
|
Back: Nonnegative.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002410-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
How is $\omega(g(n))$ defined?
|
|
Back: $\{ \forall c > 0, \exists n_0 > 0, \forall n \geq n_0, 0 \leq cg(n) < f(n) \}$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002414-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Cloze
|
|
In $\Omega(g(n))$, bound {1:$0 \leq cg(n) \leq f(n)$} holds for {1:some $c > 0$}. In $\omega(g(n))$, {2:$0 \leq cg(n) < f(n)$} holds for {2:all $c > 0$}.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002420-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
Is $\omega$-notation considered stronger or weaker than $\Omega$-notation?
|
|
Back: Stronger.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709519002425-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What condition must $g(n)$ satisfy such that $\omega(g(n))$ is nonempty?
|
|
Back: $g(n)$ must be asymptotically positive.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709750359826-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What is the transitive property of $\omega$-notation?
|
|
Back: $f(n) = \omega(g(n))$ and $g(n) = \omega(h(n))$ implies $f(n) = \omega(h(n))$.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223531-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What is the reflexive property of $\omega$-notation?
|
|
Back: N/A
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223537-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
*Why* is there no reflexive property of $\omega$-notation?
|
|
Back: A function cannot be asymptotically larger than itself.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223544-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What is the symmetric property of $\omega$-notation?
|
|
Back: N/A
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223553-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
What is the transpose symmetric property of $\omega$-notation?
|
|
Back: $f(n) = \omega(g(n))$ iff $g(n) = o(f(n))$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223563-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
$\omega$-notation is likened to what comparison operator of real numbers?
|
|
Back: $>$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223570-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Cloze
|
|
{1:$O$}-notation is to {2:$\leq$} whereas {2:$\omega$}-notation is to {1:$>$}.
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223577-->
|
|
END%%
|
|
|
|
%%ANKI
|
|
Basic
|
|
How do we set theoretically say $f(n)$ is asymptotically larger than $g(n)$?
|
|
Back: $f(n) = \omega(g(n))$
|
|
Reference: Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009).
|
|
<!--ID: 1709752223586-->
|
|
END%%
|
|
|
|
## References
|
|
|
|
* Thomas H. Cormen et al., *Introduction to Algorithms*, 3rd ed (Cambridge, Mass: MIT Press, 2009). |