deploy
|
Before Width: | Height: | Size: 10 KiB After Width: | Height: | Size: 11 KiB |
|
Before Width: | Height: | Size: 14 KiB After Width: | Height: | Size: 13 KiB |
|
Before Width: | Height: | Size: 20 KiB After Width: | Height: | Size: 22 KiB |
|
Before Width: | Height: | Size: 22 KiB After Width: | Height: | Size: 24 KiB |
|
Before Width: | Height: | Size: 13 KiB After Width: | Height: | Size: 15 KiB |
|
Before Width: | Height: | Size: 24 KiB After Width: | Height: | Size: 27 KiB |
|
Before Width: | Height: | Size: 19 KiB After Width: | Height: | Size: 20 KiB |
|
Before Width: | Height: | Size: 18 KiB After Width: | Height: | Size: 19 KiB |
|
Before Width: | Height: | Size: 21 KiB After Width: | Height: | Size: 23 KiB |
|
Before Width: | Height: | Size: 26 KiB After Width: | Height: | Size: 28 KiB |
|
Before Width: | Height: | Size: 15 KiB After Width: | Height: | Size: 17 KiB |
@@ -4382,8 +4382,8 @@
|
||||
<p>Let the size of the input data be <span class="arithmatex">\(n\)</span>, the following chart displays common types of space complexities (arranged from low to high).</p>
|
||||
<div class="arithmatex">\[
|
||||
\begin{aligned}
|
||||
O(1) < O(\log n) < O(n) < O(n^2) < O(2^n) \newline
|
||||
\text{Constant Order} < \text{Logarithmic Order} < \text{Linear Order} < \text{Quadratic Order} < \text{Exponential Order}
|
||||
& O(1) < O(\log n) < O(n) < O(n^2) < O(2^n) \newline
|
||||
& \text{Constant} < \text{Logarithmic} < \text{Linear} < \text{Quadratic} < \text{Exponential}
|
||||
\end{aligned}
|
||||
\]</div>
|
||||
<p><a class="glightbox" href="../space_complexity.assets/space_complexity_common_types.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="Common types of space complexity" class="animation-figure" src="../space_complexity.assets/space_complexity_common_types.png" /></a></p>
|
||||
|
||||
|
Before Width: | Height: | Size: 20 KiB After Width: | Height: | Size: 22 KiB |
|
Before Width: | Height: | Size: 19 KiB After Width: | Height: | Size: 20 KiB |
|
Before Width: | Height: | Size: 16 KiB After Width: | Height: | Size: 18 KiB |
|
Before Width: | Height: | Size: 19 KiB After Width: | Height: | Size: 20 KiB |
|
Before Width: | Height: | Size: 21 KiB After Width: | Height: | Size: 23 KiB |
|
Before Width: | Height: | Size: 19 KiB After Width: | Height: | Size: 21 KiB |
|
Before Width: | Height: | Size: 22 KiB After Width: | Height: | Size: 23 KiB |
|
Before Width: | Height: | Size: 12 KiB After Width: | Height: | Size: 14 KiB |
@@ -4697,8 +4697,8 @@ T(n) & = n^2 + n & \text{Simplified Count (o.O)}
|
||||
<p>Let's consider the input data size as <span class="arithmatex">\(n\)</span>. The common types of time complexities are illustrated below, arranged from lowest to highest:</p>
|
||||
<div class="arithmatex">\[
|
||||
\begin{aligned}
|
||||
O(1) < O(\log n) < O(n) < O(n \log n) < O(n^2) < O(2^n) < O(n!) \newline
|
||||
\text{Constant Order} < \text{Logarithmic Order} < \text{Linear Order} < \text{Linear-Logarithmic Order} < \text{Quadratic Order} < \text{Exponential Order} < \text{Factorial Order}
|
||||
& O(1) < O(\log n) < O(n) < O(n \log n) < O(n^2) < O(2^n) < O(n!) \newline
|
||||
& \text{Constant} < \text{Log} < \text{Linear} < \text{Linear-Log} < \text{Quadratic} < \text{Exp} < \text{Factorial}
|
||||
\end{aligned}
|
||||
\]</div>
|
||||
<p><a class="glightbox" href="../time_complexity.assets/time_complexity_common_types.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="Common types of time complexity" class="animation-figure" src="../time_complexity.assets/time_complexity_common_types.png" /></a></p>
|
||||
|
||||