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和声熵 - 版本历史
2026-06-09T23:57:21Z
本wiki上该页面的版本历史
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Administrator：/* 另见 */
2026-03-30T03:36:21Z
<p><span class="autocomment">另见</span></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">←上一版本</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">2026年3月30日 (一) 11:36的版本</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l38">第38行：</td>
<td colspan="2" class="diff-lineno">第38行：</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== 另见 ==</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== 另见 ==</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;"></del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [[Zeta调律]]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [[Zeta调律]]</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [[频谱熵]] </div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* [[频谱熵]] </div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;"></del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[Category:连续音高]]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[Category:连续音高]]</div></td></tr>
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Administrator
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2026年3月30日 (一) 03:35 Administrator
2026-03-30T03:35:54Z
<p></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">←上一版本</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">2026年3月30日 (一) 11:35的版本</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l36">第36行：</td>
<td colspan="2" class="diff-lineno">第36行：</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>红色曲线在1.5处值较小，其对应和弦为16:24:25. 这说明限制质数限会清除本来不和谐的和弦周围的和弦，从而降低其和声熵，因此限制质数限的做法应该视为简化计算的方式，而非对于某种“p限和谐度”的逼近。</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>红色曲线在1.5处值较小，其对应和弦为16:24:25. 这说明限制质数限会清除本来不和谐的和弦周围的和弦，从而降低其和声熵，因此限制质数限的做法应该视为简化计算的方式，而非对于某种“p限和谐度”的逼近。</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">== 另见 ==</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [[Zeta调律]]</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [[频谱熵]] </ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">[[Category:连续音高]]</ins></div></td></tr>
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Administrator
https://tun.wiki/index.php?title=%E5%92%8C%E5%A3%B0%E7%86%B5&diff=534&oldid=prev
Null：/* 数据 */
2026-03-17T03:52:44Z
<p><span class="autocomment">数据</span></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
<col class="diff-marker" />
<col class="diff-content" />
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<tr class="diff-title" lang="zh-Hans-CN">
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">←上一版本</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">2026年3月17日 (二) 11:52的版本</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l31">第31行：</td>
<td colspan="2" class="diff-lineno">第31行：</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>当模板和弦的个数有限且扰动的标准差σ趋于0时，平面上表示纯律和弦的点的 [https://mathworld.wolfram.com/VoronoiDiagram.html Voronoi 图] 的每个胞腔区域内对这个胞腔内的最邻近点的置信程度趋于1，而胞腔边缘和顶点则不是。这张图虽然考虑了无穷多模板和弦，但是效果上类似于模板和弦的个数有限。</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>当模板和弦的个数有限且扰动的标准差σ趋于0时，平面上表示纯律和弦的点的 [https://mathworld.wolfram.com/VoronoiDiagram.html Voronoi 图] 的每个胞腔区域内对这个胞腔内的最邻近点的置信程度趋于1，而胞腔边缘和顶点则不是。这张图虽然考虑了无穷多模板和弦，但是效果上类似于模板和弦的个数有限。</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>以下是三音和弦1:x:3/2的和声熵，其中x为横坐标，模板和弦为3音纯律和弦，质数限为5或7；先验概率为<math>P(X_n)=1/(X_{n1}X_{n2}X_{n3})^2</math>；观测误差<math>\epsilon_1, ..., \epsilon_n</math><del style="font-weight: bold; text-decoration: none;">为正态分布随机变量，均值为0，标准差为9[[间差]](21.51¢)；置信程度取</del><math>\max_x f(x)</math>. 和声熵数据的误差不超过0.005.</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>以下是三音和弦1:x:3/2的和声熵，其中x为横坐标，模板和弦为3音纯律和弦，质数限为5或7；先验概率为<math>P(X_n)=1/(X_{n1}X_{n2}X_{n3})^2</math>；观测误差<math>\epsilon_1, ..., \epsilon_n</math><ins style="font-weight: bold; text-decoration: none;">为正态分布随机变量，均值为0，标准差为9间差；置信程度取</ins><math>\max_x f(x)</math>. 和声熵数据的误差不超过0.005.</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[文件:13532.png|3音和弦的和声熵]]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[文件:13532.png|3音和弦的和声熵]]</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>红色曲线在1.5处值较小，其对应和弦为16:24:25. 这说明限制质数限会清除本来不和谐的和弦周围的和弦，从而降低其和声熵，因此限制质数限的做法应该视为简化计算的方式，而非对于某种“p限和谐度”的逼近。</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>红色曲线在1.5处值较小，其对应和弦为16:24:25. 这说明限制质数限会清除本来不和谐的和弦周围的和弦，从而降低其和声熵，因此限制质数限的做法应该视为简化计算的方式，而非对于某种“p限和谐度”的逼近。</div></td></tr>
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Null
https://tun.wiki/index.php?title=%E5%92%8C%E5%A3%B0%E7%86%B5&diff=533&oldid=prev
Null：/* 数据 */
2026-03-17T03:52:25Z
<p><span class="autocomment">数据</span></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
<col class="diff-marker" />
<col class="diff-content" />
<col class="diff-marker" />
<col class="diff-content" />
<tr class="diff-title" lang="zh-Hans-CN">
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">←上一版本</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">2026年3月17日 (二) 11:52的版本</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l35">第35行：</td>
<td colspan="2" class="diff-lineno">第35行：</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[文件:13532.png|3音和弦的和声熵]]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[[文件:13532.png|3音和弦的和声熵]]</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>红色曲线在1.5处值较小，其对应和弦为16:24:25.</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>红色曲线在1.5处值较小，其对应和弦为16:24:25. <ins style="font-weight: bold; text-decoration: none;">这说明限制质数限会清除本来不和谐的和弦周围的和弦，从而降低其和声熵，因此限制质数限的做法应该视为简化计算的方式，而非对于某种“p限和谐度”的逼近。</ins></div></td></tr>
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Null
https://tun.wiki/index.php?title=%E5%92%8C%E5%A3%B0%E7%86%B5&diff=532&oldid=prev
Null：/* 数据 */
2026-03-17T03:44:21Z
<p><span class="autocomment">数据</span></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
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<tr class="diff-title" lang="zh-Hans-CN">
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">←上一版本</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">2026年3月17日 (二) 11:44的版本</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l30">第30行：</td>
<td colspan="2" class="diff-lineno">第30行：</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>当模板和弦的个数有限且扰动的标准差σ趋于0时，平面上表示纯律和弦的点的 [https://mathworld.wolfram.com/VoronoiDiagram.html Voronoi 图] 的每个胞腔区域内对这个胞腔内的最邻近点的置信程度趋于1，而胞腔边缘和顶点则不是。这张图虽然考虑了无穷多模板和弦，但是效果上类似于模板和弦的个数有限。</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>当模板和弦的个数有限且扰动的标准差σ趋于0时，平面上表示纯律和弦的点的 [https://mathworld.wolfram.com/VoronoiDiagram.html Voronoi 图] 的每个胞腔区域内对这个胞腔内的最邻近点的置信程度趋于1，而胞腔边缘和顶点则不是。这张图虽然考虑了无穷多模板和弦，但是效果上类似于模板和弦的个数有限。</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">以下是三音和弦1:x:3/2的和声熵，其中x为横坐标，模板和弦为3音纯律和弦，质数限为5或7；先验概率为<math>P(X_n)=1/(X_{n1}X_{n2}X_{n3})^2</math>；观测误差<math>\epsilon_1, ..., \epsilon_n</math>为正态分布随机变量，均值为0，标准差为9[[间差]](21.51¢)；置信程度取<math>\max_x f(x)</math>. 和声熵数据的误差不超过0.005.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">[[文件:13532.png|3音和弦的和声熵]]</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">红色曲线在1.5处值较小，其对应和弦为16:24:25.</ins></div></td></tr>
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Null
https://tun.wiki/index.php?title=%E5%92%8C%E5%A3%B0%E7%86%B5&diff=521&oldid=prev
Null：/* 细节 */
2026-03-17T02:43:14Z
<p><span class="autocomment">细节</span></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
<col class="diff-marker" />
<col class="diff-content" />
<col class="diff-marker" />
<col class="diff-content" />
<tr class="diff-title" lang="zh-Hans-CN">
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">←上一版本</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">2026年3月17日 (二) 10:43的版本</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l13">第13行：</td>
<td colspan="2" class="diff-lineno">第13行：</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* 模板和弦的集合<math>X=\{ X_n\}</math>可以取[[整数限]]和[[质数限]]有限的和弦，或者质数限有限的和弦，或者一切k音纯律和弦。如果选择第一个选项，<math>P(X_n)</math>可以任意选择；如果选择第二个选项，<math>P(X_n)</math>可以选择为<math>1/s(X_n)^\beta</math>, 其中<math>s(X_n)</math>表示<math>X_n</math>的整数限，<math>\beta</math>为大于0的常数；如果选择第三个选项，<math>P(X_n)</math>可以选择为<math>1/(X_{n1}X_{n2}...X_{nk})^\beta</math>,<math>\beta</math>大于1的常数，这里要求<math>X_{n1}, X_{n2}, ...,X_{nk}</math>是正整数且没有大于1的公因子。</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* 模板和弦的集合<math>X=\{ X_n\}</math>可以取[[整数限]]和[[质数限]]有限的和弦，或者质数限有限的和弦，或者一切k音纯律和弦。如果选择第一个选项，<math>P(X_n)</math>可以任意选择；如果选择第二个选项，<math>P(X_n)</math>可以选择为<math>1/s(X_n)^\beta</math>, 其中<math>s(X_n)</math>表示<math>X_n</math>的整数限，<math>\beta</math>为大于0的常数；如果选择第三个选项，<math>P(X_n)</math>可以选择为<math>1/(X_{n1}X_{n2}...X_{nk})^\beta</math>,<math>\beta</math>大于1的常数，这里要求<math>X_{n1}, X_{n2}, ...,X_{nk}</math>是正整数且没有大于1的公因子。</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>* 以上三种选择和弦的方式会给[[泛音列]]<del style="font-weight: bold; text-decoration: none;">的靠近基音的子集较低的和声熵，[[泛音列]]的远离基音的子集较高的和声熵。</del></div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>* 以上三种选择和弦的方式会给[[泛音列]]<ins style="font-weight: bold; text-decoration: none;">的靠近基音的子集较低的和声熵，泛音列的远离基音的子集较高的和声熵。</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* 鉴于人耳的对音程的识别误差可以用[[音分]]而不是赫兹数表示，假设<math>X_n</math>的音分为<math>x_1</math>¢,...,<math>x_k</math>¢, <math>Y</math>的音分为<math>y_1</math>¢,...,<math>y_k</math>¢, 则<math>y_1=x_1+\epsilon_1</math>, ..., <math>y_k=x_k+\epsilon_k</math>，其中<math>\epsilon_1, ..., \epsilon_n</math>为独立同分布的正态随机变量，其均值为0，其标准差是自由参数σ。</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* 鉴于人耳的对音程的识别误差可以用[[音分]]而不是赫兹数表示，假设<math>X_n</math>的音分为<math>x_1</math>¢,...,<math>x_k</math>¢, <math>Y</math>的音分为<math>y_1</math>¢,...,<math>y_k</math>¢, 则<math>y_1=x_1+\epsilon_1</math>, ..., <math>y_k=x_k+\epsilon_k</math>，其中<math>\epsilon_1, ..., \epsilon_n</math>为独立同分布的正态随机变量，其均值为0，其标准差是自由参数σ。</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* 计算<math>P(Y|X_n)</math>的方式如下：将<math>X_n</math>写成音分<math>x_1</math>¢, ..., <math>x_k</math>¢, <math>Y</math>写成音分<math>y_1</math>¢, ..., <math>y_k</math>¢, 顺序为从小到大，且使得<math>x_1+...+x_k=y_1+...+y_k</math> (这相当于给和弦的频率比的每一项乘以一个常数)，则<math>P(Y|X_n)</math>正比于<math>\exp(-((x_1-y_1)^2+...+(x_k-y_k)^2)/{2\sigma^2})</math>.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* 计算<math>P(Y|X_n)</math>的方式如下：将<math>X_n</math>写成音分<math>x_1</math>¢, ..., <math>x_k</math>¢, <math>Y</math>写成音分<math>y_1</math>¢, ..., <math>y_k</math>¢, 顺序为从小到大，且使得<math>x_1+...+x_k=y_1+...+y_k</math> (这相当于给和弦的频率比的每一项乘以一个常数)，则<math>P(Y|X_n)</math>正比于<math>\exp(-((x_1-y_1)^2+...+(x_k-y_k)^2)/{2\sigma^2})</math>.</div></td></tr>
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Null
https://tun.wiki/index.php?title=%E5%92%8C%E5%A3%B0%E7%86%B5&diff=520&oldid=prev
Null：/* 细节 */
2026-03-17T02:22:42Z
<p><span class="autocomment">细节</span></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
<col class="diff-marker" />
<col class="diff-content" />
<col class="diff-marker" />
<col class="diff-content" />
<tr class="diff-title" lang="zh-Hans-CN">
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">←上一版本</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">2026年3月17日 (二) 10:22的版本</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l13">第13行：</td>
<td colspan="2" class="diff-lineno">第13行：</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* 模板和弦的集合<math>X=\{ X_n\}</math>可以取[[整数限]]和[[质数限]]有限的和弦，或者质数限有限的和弦，或者一切k音纯律和弦。如果选择第一个选项，<math>P(X_n)</math>可以任意选择；如果选择第二个选项，<math>P(X_n)</math>可以选择为<math>1/s(X_n)^\beta</math>, 其中<math>s(X_n)</math>表示<math>X_n</math>的整数限，<math>\beta</math>为大于0的常数；如果选择第三个选项，<math>P(X_n)</math>可以选择为<math>1/(X_{n1}X_{n2}...X_{nk})^\beta</math>,<math>\beta</math>大于1的常数，这里要求<math>X_{n1}, X_{n2}, ...,X_{nk}</math>是正整数且没有大于1的公因子。</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* 模板和弦的集合<math>X=\{ X_n\}</math>可以取[[整数限]]和[[质数限]]有限的和弦，或者质数限有限的和弦，或者一切k音纯律和弦。如果选择第一个选项，<math>P(X_n)</math>可以任意选择；如果选择第二个选项，<math>P(X_n)</math>可以选择为<math>1/s(X_n)^\beta</math>, 其中<math>s(X_n)</math>表示<math>X_n</math>的整数限，<math>\beta</math>为大于0的常数；如果选择第三个选项，<math>P(X_n)</math>可以选择为<math>1/(X_{n1}X_{n2}...X_{nk})^\beta</math>,<math>\beta</math>大于1的常数，这里要求<math>X_{n1}, X_{n2}, ...,X_{nk}</math>是正整数且没有大于1的公因子。</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* 以上三种选择和弦的方式会给[[泛音列]]的靠近基音的子集较低的和声熵，[[泛音列]]的远离基音的子集较高的和声熵。</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* 鉴于人耳的对音程的识别误差可以用[[音分]]而不是赫兹数表示，假设<math>X_n</math>的音分为<math>x_1</math>¢,...,<math>x_k</math>¢, <math>Y</math>的音分为<math>y_1</math>¢,...,<math>y_k</math>¢, 则<math>y_1=x_1+\epsilon_1</math>, ..., <math>y_k=x_k+\epsilon_k</math>，其中<math>\epsilon_1, ..., \epsilon_n</math>为独立同分布的正态随机变量，其均值为0，其标准差是自由参数σ。</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* 鉴于人耳的对音程的识别误差可以用[[音分]]而不是赫兹数表示，假设<math>X_n</math>的音分为<math>x_1</math>¢,...,<math>x_k</math>¢, <math>Y</math>的音分为<math>y_1</math>¢,...,<math>y_k</math>¢, 则<math>y_1=x_1+\epsilon_1</math>, ..., <math>y_k=x_k+\epsilon_k</math>，其中<math>\epsilon_1, ..., \epsilon_n</math>为独立同分布的正态随机变量，其均值为0，其标准差是自由参数σ。</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* 计算<math>P(Y|X_n)</math>的方式如下：将<math>X_n</math>写成音分<math>x_1</math>¢, ..., <math>x_k</math>¢, <math>Y</math>写成音分<math>y_1</math>¢, ..., <math>y_k</math>¢, 顺序为从小到大，且使得<math>x_1+...+x_k=y_1+...+y_k</math> (这相当于给和弦的频率比的每一项乘以一个常数)，则<math>P(Y|X_n)</math>正比于<math>\exp(-((x_1-y_1)^2+...+(x_k-y_k)^2)/{2\sigma^2})</math>.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* 计算<math>P(Y|X_n)</math>的方式如下：将<math>X_n</math>写成音分<math>x_1</math>¢, ..., <math>x_k</math>¢, <math>Y</math>写成音分<math>y_1</math>¢, ..., <math>y_k</math>¢, 顺序为从小到大，且使得<math>x_1+...+x_k=y_1+...+y_k</math> (这相当于给和弦的频率比的每一项乘以一个常数)，则<math>P(Y|X_n)</math>正比于<math>\exp(-((x_1-y_1)^2+...+(x_k-y_k)^2)/{2\sigma^2})</math>.</div></td></tr>
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Null
https://tun.wiki/index.php?title=%E5%92%8C%E5%A3%B0%E7%86%B5&diff=519&oldid=prev
Null：/* 数据 */
2026-03-17T01:51:13Z
<p><span class="autocomment">数据</span></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
<col class="diff-marker" />
<col class="diff-content" />
<col class="diff-marker" />
<col class="diff-content" />
<tr class="diff-title" lang="zh-Hans-CN">
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">←上一版本</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">2026年3月17日 (二) 09:51的版本</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l23">第23行：</td>
<td colspan="2" class="diff-lineno">第23行：</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== 数据 ==</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== 数据 ==</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>以下是三音和弦1:x:y的和声熵，其中x,y分别为横纵坐标，模板和弦为所有的3音纯律和弦，先验概率为<math>P(X_n)=1/(X_{n1}X_{n2}X_{n3})^2</math>；观测误差<math>\epsilon_1, ..., \epsilon_n</math>为正态分布随机变量，均值为0，标准差为9[[间差]](21.51¢)；置信程度取<math>\max_x f(x)</math>. 和声熵数据的误差不超过0.005.</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>以下是三音和弦1:x:y的和声熵，其中x, y分别为横纵坐标，模板和弦为所有的3音纯律和弦，先验概率为<math>P(X_n)=1/(X_{n1}X_{n2}X_{n3})^2</math>；观测误差<math>\epsilon_1, ..., \epsilon_n</math>为正态分布随机变量，均值为0，标准差为9[[间差]](21.51¢)；置信程度取<math>\max_x f(x)</math>. 和声熵数据的误差不超过0.005.</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
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https://tun.wiki/index.php?title=%E5%92%8C%E5%A3%B0%E7%86%B5&diff=518&oldid=prev
Null：/* 数据 */
2026-03-17T01:50:56Z
<p><span class="autocomment">数据</span></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
<col class="diff-marker" />
<col class="diff-content" />
<col class="diff-marker" />
<col class="diff-content" />
<tr class="diff-title" lang="zh-Hans-CN">
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">←上一版本</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">2026年3月17日 (二) 09:50的版本</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l23">第23行：</td>
<td colspan="2" class="diff-lineno">第23行：</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== 数据 ==</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== 数据 ==</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">以下是三音和弦的和声熵，其中模板和弦为所有的3音纯律和弦，先验概率为</del><math>P(X_n)=1/(X_{n1}X_{n2}X_{n3})^2</math>；观测误差<math>\epsilon_1, ..., \epsilon_n</math>为正态分布随机变量，均值为0，标准差为9[[间差]](21.51¢)；置信程度取<math>\max_x f(x)</math>. 和声熵数据的误差不超过0.005.</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">以下是三音和弦1:x:y的和声熵，其中x,y分别为横纵坐标，模板和弦为所有的3音纯律和弦，先验概率为</ins><math>P(X_n)=1/(X_{n1}X_{n2}X_{n3})^2</math>；观测误差<math>\epsilon_1, ..., \epsilon_n</math>为正态分布随机变量，均值为0，标准差为9[[间差]](21.51¢)；置信程度取<math>\max_x f(x)</math>. 和声熵数据的误差不超过0.005.</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
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Null
https://tun.wiki/index.php?title=%E5%92%8C%E5%A3%B0%E7%86%B5&diff=517&oldid=prev
Null：/* 性质 */
2026-03-17T01:33:36Z
<p><span class="autocomment">性质</span></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
<col class="diff-marker" />
<col class="diff-content" />
<col class="diff-marker" />
<col class="diff-content" />
<tr class="diff-title" lang="zh-Hans-CN">
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">←上一版本</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">2026年3月17日 (二) 09:33的版本</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l18">第18行：</td>
<td colspan="2" class="diff-lineno">第18行：</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== 性质 ==</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== 性质 ==</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* 和声熵只取决于和弦的频率比，不取决于音区（和弦的频率）和音色。</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* 和声熵只取决于和弦的频率比，不取决于音区（和弦的频率）和音色。</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* 计算和声熵需要预先知道k的值，当k很大时(≥4)，计算和声熵将变得困难。</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* 和声熵并不会因为和弦的两个音趋于相同而减少，这是因为让两音相同会远离模板和弦。</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* 和声熵并不会因为和弦的两个音趋于相同而减少，这是因为让两音相同会远离模板和弦。</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* 使用和声熵时可以拒绝承认某个素数具有和声意义，只要在模板和弦里删除包含这一素数因子的和弦即可。</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* 使用和声熵时可以拒绝承认某个素数具有和声意义，只要在模板和弦里删除包含这一素数因子的和弦即可。</div></td></tr>
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