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2026-04-13 18:00:18 +08:00 · 2023-09-21 20:44:52 +08:00
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@@ -3622,7 +3622,32 @@
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 <h1 id="23">2.3 &nbsp; 时间复杂度<a class="headerlink" href="#23" title="Permanent link">&para;</a></h1>
 <p>运行时间可以直观且准确地反映算法的效率。如果我们想要准确预估一段代码的运行时间，应该如何操作呢？</p>
 <ol>
@@ -6583,11 +6615,73 @@ n! = n \times (n - 1) \times (n - 2) \times \dots \times 2 \times 1
 <p>可能由于 <span class="arithmatex">\(O\)</span> 符号过于朗朗上口，我们常常使用它来表示平均时间复杂度。但从严格意义上看，这种做法并不规范。在本书和其他资料中，若遇到类似“平均时间复杂度 <span class="arithmatex">\(O(n)\)</span>”的表述，请将其直接理解为 <span class="arithmatex">\(\Theta(n)\)</span> 。</p>
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@@ -6653,48 +6747,31 @@ n! = n \times (n - 1) \times (n - 2) \times \dots \times 2 \times 1
        
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@@ -6705,6 +6782,8 @@ n! = n \times (n - 1) \times (n - 2) \times \dots \times 2 \times 1
  
  
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