Sliding Window Maximum 解答

本文介绍了一种在给定数组中找到滑动窗口内的最大整数的方法,使用双端队列来实现O(n)时间复杂度和O(k)空间复杂度。

摘要生成于 C知道 ,由 DeepSeek-R1 满血版支持, 前往体验 >

Question

Given an array of n integer with duplicate number, and a moving window(size k), move the window at each iteration from the start of the array, find the maximum number inside the window at each moving.

Example

For array [1, 2, 7, 7, 8], moving window size k = 3. return [7, 7, 8]

At first the window is at the start of the array like this

[|1, 2, 7| ,7, 8] , return the maximum 7;

then the window move one step forward.

[1, |2, 7 ,7|, 8], return the maximum 7;

then the window move one step forward again.

[1, 2, |7, 7, 8|], return the maximum 8;

Challenge

o(n) time and O(k) memory

Solution

Key to the solution is to maintain a deque (size <= k) whose elements are always in descending order. Then, the first element is what we want.

Every time we want to add a new element, we need to check:

1. whether it is bigger than previous elements in deque.

If yes, we remove elements in deque which are smaller than current element.

2. whether the first element in deque is out of current sliding window.

If yes, we remove first element.

 1 public class Solution {
 2     
 3     public ArrayList<Integer> maxSlidingWindow(int[] nums, int k) {
 4         ArrayList<Integer> result = new ArrayList<Integer>();
 5         Deque<Integer> deque = new LinkedList<Integer>();
 6         int i = 0;
 7         for (int current : nums) {
 8             i++;
 9             // Ensure current deque is in decending order
10             while (!deque.isEmpty() && deque.peekLast() < current)
11                 deque.pollLast();
12             deque.addLast(current);
13             if (i > k && deque.peekFirst() == nums[i - k - 1])
14                 deque.pollFirst();
15             if (i >= k)
16                 result.add(deque.peekFirst());
17         }
18         return result;
19     }
20 }

 

转载于:https://www.cnblogs.com/ireneyanglan/p/4908033.html

评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值