Formatted question description: https://leetcode.ca/all/1911.html

# 1911. Maximum Alternating Subsequence Sum

Medium

## Description

The alternating sum of a 0-indexed array is defined as the sum of the elements at even indices minus the sum of the elements at odd indices.

• For example, the alternating sum of [4,2,5,3] is (4 + 5) - (2 + 3) = 4.

Given an array nums, return the maximum alternating sum of any subsequence of nums (after reindexing the elements of the subsequence).

A subsequence of an array is a new array generated from the original array by deleting some elements (possibly none) without changing the remaining elements’ relative order. For example, [2,7,4] is a subsequence of [4,2,3,7,2,1,4], while [2,4,2] is not.

Example 1:

Input: nums = [4,2,5,3]

Output: 7

Explanation: It is optimal to choose the subsequence [4,2,5] with alternating sum (4 + 5) - 2 = 7.

Example 2:

Input: nums = [5,6,7,8]

Output: 8

Explanation: It is optimal to choose the subsequence [8] with alternating sum 8.

Example 3:

Input: nums = [6,2,1,2,4,5]

Output: 10

Explanation: It is optimal to choose the subsequence [6,1,5] with alternating sum (6 + 5) - 1 = 10.

Constraints:

• 1 <= nums.length <= 10^5
• 1 <= nums[i] <= 10^5

## Solution

Use dynamic programming. For 0 <= i < nums.length, let dp[i][0] represent the maximum alternating subsequence sum at index i when nums[i] is used as an even index or not used, and dp[i][1] represent the maximum alternating subsequence sum at index i when nums[i] is used as an odd index or not used.

Initially, dp[0][0] = nums[0] and dp[0][1] = 0 (since all elements in nums are nonnegative). For 1 <= i < nums.length, there exist relations dp[i][0] = Math.max(Math.max(dp[i - 1][1], 0) + nums[i], dp[i - 1][0]) and dp[i][1] = Math.max(Math.max(dp[i - 1][0] - nums[i], 0), dp[i - 1][1]).

Finally, return the maximum of dp[nums.length - 1][0] and dp[nums.length - 1][1].

class Solution {
public long maxAlternatingSum(int[] nums) {
int length = nums.length;
long[][] dp = new long[length][2];
dp[0][0] = nums[0];
for (int i = 1; i < length; i++) {
dp[i][0] = Math.max(Math.max(dp[i - 1][1], 0) + nums[i], dp[i - 1][0]);
dp[i][1] = Math.max(Math.max(dp[i - 1][0] - nums[i], 0), dp[i - 1][1]);
}
return Math.max(dp[length - 1][0], dp[length - 1][1]);
}
}