minimum-size-subarray-sum

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Algorithms

Given an array of positive integers <code>nums</code> and a positive integer <code>target</code>, return the minimal length of a subarray whose sum is greater than or equal to <code>target</code>. If there is no such subarray, return <code>0</code> instead.

&nbsp;
Example 1:

<pre>
Input: target = 7, nums = [2,3,1,2,4,3]
Output: 2
Explanation: The subarray [4,3] has the minimal length under the problem constraint.
</pre>

Example 2:

<pre>
Input: target = 4, nums = [1,4,4]
Output: 1
</pre>

Example 3:

<pre>
Input: target = 11, nums = [1,1,1,1,1,1,1,1]
Output: 0
</pre>

&nbsp;
Constraints:

<ul>
	<li><code>1 &lt;= target &lt;= 109</code></li>
	<li><code>1 &lt;= nums.length &lt;= 105</code></li>
	<li><code>1 &lt;= nums[i] &lt;= 104</code></li>
</ul>

&nbsp;
Follow up: If you have figured out the <code>O(n)</code> solution, try coding another solution of which the time complexity is <code>O(n log(n))</code>.

minSubArrayLen

Minimum Size Subarray Sum

Minimum Window Substring

minimum-window-substring

最小覆盖子串

Maximum Size Subarray Sum Equals k

maximum-size-subarray-sum-equals-k

和等于 k 的最长子数组长度

Maximum Length of Repeated Subarray

maximum-length-of-repeated-subarray

最长重复子数组

Minimum Operations to Reduce X to Zero

minimum-operations-to-reduce-x-to-zero

将 x 减到 0 的最小操作数

K Radius Subarray Averages

k-radius-subarray-averages

半径为 k 的子数组平均值

Maximum Product After K Increments

maximum-product-after-k-increments

K 次增加后的最大乘积

Shortest Subarray With OR at Least K I

shortest-subarray-with-or-at-least-k-i

或值至少 K 的最短子数组 I

Minimum Positive Sum Subarray 

minimum-positive-sum-subarray

最小正和子数组

Array

Binary Search

Prefix Sum

Sliding Window

给定一个含有&nbsp;<code>n</code>&nbsp;个正整数的数组和一个正整数 <code>target</code> 。

找出该数组中满足其总和大于等于 <code>target</code> 的长度最小的 子数组&nbsp;<code>[numsl, numsl+1, ..., numsr-1, numsr]</code> ，并返回其长度。如果不存在符合条件的子数组，返回 <code>0</code> 。

&nbsp;

示例 1：

<pre>
输入：target = 7, nums = [2,3,1,2,4,3]
输出：2
解释：子数组&nbsp;<code>[4,3]</code>&nbsp;是该条件下的长度最小的子数组。
</pre>

示例 2：

<pre>
输入：target = 4, nums = [1,4,4]
输出：1
</pre>

示例 3：

<pre>
输入：target = 11, nums = [1,1,1,1,1,1,1,1]
输出：0
</pre>

&nbsp;

提示：

<ul>
	<li><code>1 &lt;= target &lt;= 109</code></li>
	<li><code>1 &lt;= nums.length &lt;= 105</code></li>
	<li><code>1 &lt;= nums[i] &lt;= 104</code></li>
</ul>

&nbsp;

进阶：

<ul>
	<li>如果你已经实现 <code>O(n)</code> 时间复杂度的解法, 请尝试设计一个 <code>O(n log(n))</code> 时间复杂度的解法。</li>
</ul>