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添加了二维数组版本,相比于一维好理解

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`@@ -210,6 +210,45 @@ class Solution {`
`210`	`210`	`}`
`211`	`211`	```
`212`	`212`
	`213`	`+二维数组版本(易于理解):`
	`214`	+```Java
	`215`	`+class Solution {`
	`216`	`+ public boolean canPartition(int[] nums) {`
	`217`	`+ int sum = 0;`
	`218`	`+ for (int i = 0; i < nums.length; i++) {`
	`219`	`+ sum += nums[i];`
	`220`	`+ }`
	`221`	`+`
	`222`	`+ if (sum % 2 == 1)`
	`223`	`+ return false;`
	`224`	`+ int target = sum / 2;`
	`225`	`+`
	`226`	`+ //dp[i][j]代表可装物品为0-i,背包容量为j的情况下,背包内容量的最大价值`
	`227`	`+ int[][] dp = new int[nums.length][target + 1];`
	`228`	`+`
	`229`	`+ //初始化,dp[0][j]的最大价值nums[0](if j > weight[i])`
	`230`	`+ //dp[i][0]均为0,不用初始化`
	`231`	`+ for (int j = nums[0]; j <= target; j++) {`
	`232`	`+ dp[0][j] = nums[0];`
	`233`	`+ }`
	`234`	`+`
	`235`	`+ //遍历物品,遍历背包`
	`236`	`+ //递推公式:`
	`237`	`+ for (int i = 1; i < nums.length; i++) {`
	`238`	`+ for (int j = 0; j <= target; j++) {`
	`239`	`+ //背包容量可以容纳nums[i]`
	`240`	`+ if (j >= nums[i]) {`
	`241`	`+ dp[i][j] = Math.max(dp[i - 1][j], dp[i - 1][j - nums[i]] + nums[i]);`
	`242`	`+ } else {`
	`243`	`+ dp[i][j] = dp[i - 1][j];`
	`244`	`+ }`
	`245`	`+ }`
	`246`	`+ }`
	`247`	`+`
	`248`	`+ return dp[nums.length - 1][target] == target;`
	`249`	`+ }`
	`250`	`+}`
	`251`	+```
`213`	`252`	`Python:`
`214`	`253`	```python
`215`	`254`	`class Solution:`

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