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docs/chapter_dynamic_programming/dp_problem_features.md
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@ -22,7 +22,7 @@ comments: true
如图 14-6 所示，若第 $1$、$2$、$3$ 阶的代价分别为 $1$、$10$、$1$ ，则从地面爬到第 $3$ 阶的最小代价为 $2$ 。
![爬到第 3 阶的最小代价](dp_problem_features.assets/min_cost_cs_example.png)
![爬到第 3 阶的最小代价](dp_problem_features.assets/min_cost_cs_example.png){ class="animation-figure" }
<p align="center"> 图 14-6 &nbsp; 爬到第 3 阶的最小代价 </p>
@ -300,7 +300,7 @@ $$
图 14-7 展示了以上代码的动态规划过程。
![爬楼梯最小代价的动态规划过程](dp_problem_features.assets/min_cost_cs_dp.png)
![爬楼梯最小代价的动态规划过程](dp_problem_features.assets/min_cost_cs_dp.png){ class="animation-figure" }
<p align="center"> 图 14-7 &nbsp; 爬楼梯最小代价的动态规划过程 </p>
@ -545,7 +545,7 @@ $$
例如图 14-8 ，爬上第 $3$ 阶仅剩 $2$ 种可行方案，其中连续三次跳 $1$ 阶的方案不满足约束条件，因此被舍弃。
![带约束爬到第 3 阶的方案数量](dp_problem_features.assets/climbing_stairs_constraint_example.png)
![带约束爬到第 3 阶的方案数量](dp_problem_features.assets/climbing_stairs_constraint_example.png){ class="animation-figure" }
<p align="center"> 图 14-8 &nbsp; 带约束爬到第 3 阶的方案数量 </p>
@ -567,7 +567,7 @@ dp[i, 2] = dp[i-2, 1] + dp[i-2, 2]
\end{cases}
$$
![考虑约束下的递推关系](dp_problem_features.assets/climbing_stairs_constraint_state_transfer.png)
![考虑约束下的递推关系](dp_problem_features.assets/climbing_stairs_constraint_state_transfer.png){ class="animation-figure" }
<p align="center"> 图 14-9 &nbsp; 考虑约束下的递推关系 </p>