A - How to Type

Pirates have finished developing the typing software. He called Cathy to test his typing software. She is good at thinking. After testing for several days, she finds that if she types a string by some ways, she will type the key at least. But she has a bad habit that if the caps lock is on, she must turn off it, after she finishes typing. Now she wants to know the smallest times of typing the key to finish typing a string.

Input The first line is an integer t (t<=100), which is the number of test case in the input file. For each test case, there is only one string which consists of lowercase letter and upper case letter. The length of the string is at most 100. Output For each test case, you must output the smallest times of typing the key to finish typing this string. Sample Input
3
Pirates
HDUacm
HDUACM
Sample Output
8
8
8


        
  
Hint
The string “Pirates”, can type this way, Shift, p, i, r, a, t, e, s, the answer is 8.
The string “HDUacm”, can type this way, Caps lock, h, d, u, Caps lock, a, c, m, the answer is 8
The string "HDUACM", can type this way Caps lock h, d, u, a, c, m, Caps lock, the answer is 8

        
 
#include <iostream>
#include <cstdio>
#include <cstdlib>
#include <cmath>
#include <algorithm>
#include <queue>
#include <stack>
#include <vector>
#include <cstring>

using namespace std;

const int maxn = 1e4 + 10;
const int INF = 0x3f3f3f3f;
int t, n, m, ans = 0, sum;
int a[maxn][maxn], dpa[maxn], dpb[maxn];
int vis[maxn][maxn];
int dir[][2] = {{0, -1}, {0, -2}, {0, 1}, {0, 2}, {1, 0}, {2, 0}, {-1, 0}, {-2, 0} };
int main() {
    scanf("%d", &t);
    for(int i = 1; i <= t; i++) {
        char s[105];
        scanf("%s", s + 1);
        int len = strlen(s + 1) + 1;
        dpa[0] = 0; // Caps off
        dpb[0] = 1; // Caps on
        for(int j = 1; j < len; j++) {
            if(s[j] >= 'a' && s[j] <= 'z') {
                        // sc             // turn off Caps + sc
                dpa[j] = min(dpa[j - 1] + 1, dpb[j - 1] + 2);
                        // sc + turn on Caps // shift + sc 
                dpb[j] = min(dpa[j - 1] + 2, dpb[j - 1] + 2);
            } else {
                        // shift + sc       // sc + turn off Caps
                dpa[j] = min(dpa[j - 1] + 2, dpb[j - 1] + 2);
                        // turn on Caps + sc // sc
                dpb[j] = min(dpa[j - 1] + 2, dpb[j - 1] + 1);
            }
        }
        printf("%d\n", min(dpb[len - 1] + 1, dpa[len - 1]));
    }
    return 0;
}


内容概要:本文介绍了一个基于多传感器融合的定位系统设计方案,采用GPS、里程计和电子罗盘作为定位传感器,利用扩展卡尔曼滤波(EKF)算法对多源传感器数据进行融合处理,最终输出目标的滤波后位置信息,并提供了完整的Matlab代码实现。该方法有效提升了定位精度与稳定性,尤其适用于存在单一传感器误差或信号丢失的复杂环境,如自动驾驶、移动采用GPS、里程计和电子罗盘作为定位传感器,EKF作为多传感器的融合算法,最终输出目标的滤波位置(Matlab代码实现)机器人导航等领域。文中详细阐述了各传感器的数据建模方式、状态转移与观测方程构建,以及EKF算法的具体实现步骤,具有较强的工程实践价值。; 适合人群:具备一定Matlab编程基础,熟悉传感器原理和滤波算法的高校研究生、科研人员及从事自动驾驶、机器人导航等相关领域的工程技术人员。; 使用场景及目标:①学习和掌握多传感器融合的基本理论与实现方法;②应用于移动机器人、无人车、无人机等系统的高精度定位与导航开发;③作为EKF算法在实际工程中应用的教学案例或项目参考; 阅读建议:建议读者结合Matlab代码逐行理解算法实现过程,重点关注状态预测与观测更新模块的设计逻辑,可尝试引入真实传感器数据或仿真噪声环境以验证算法鲁棒性,并进一步拓展至UKF、PF等更高级滤波算法的研究与对比。
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