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Merge pull request #1 from crazy-canux/x390
update docs
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# Sphinx build info version 1 | ||
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. | ||
config: 829654fe7a7ca63a73f812f2e1a603f3 | ||
config: a212675aeb140e10a4e2b5d53fee85b8 | ||
tags: 645f666f9bcd5a90fca523b33c5a78b7 |
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.. _algorithm: | ||
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Algorithm | ||
========= | ||
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对数 | ||
---- | ||
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loga^b = x => a^x = b | ||
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loga^(mn) = loga^m + loga^n | ||
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loga^(m/n) = loga^m - loga^n | ||
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loga^(M^n) = nloga^M | ||
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loga^b = logc^b / logc^a | ||
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ln e为底 | ||
lg 10为底 | ||
log 任意底 | ||
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时间复杂度 | ||
---------- | ||
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渐进时间复杂度,表示数据规模和运算时间之间的关系。 | ||
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常见时间复杂度从小到大排列: | ||
1. O(1) 常数阶 | ||
2. O(logn) 对数阶 | ||
3. O(n) 线性阶 | ||
4. O(nlogn) 线性对数阶 | ||
5. O(n^2) 平方阶 | ||
6. O(n^3) 立方阶 | ||
7. O(2^n) 指数阶 | ||
8. O(n!) 阶乘阶 | ||
9. O(n^n) k次方阶 | ||
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空间复杂度 | ||
---------- | ||
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渐进空间复杂度,表示数据规模和算法存储空间之间的关系。 | ||
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常见空间复杂度从小到大排列: | ||
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1. O(1) | ||
2. O(n) | ||
3. O(n^2) | ||
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递归 | ||
----- | ||
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避免无限递归。 | ||
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递归条件: | ||
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* 一个问题可以分解成几个子问题。 | ||
* 问题分解之后,除了数据规模,思路是一样的。 | ||
* 存在基线或终止条件。 |
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