POJ 3267 The Cow Lexicon

本文探讨了一种解决牛群间通信中噪声干扰的问题,即确定收到消息中需要删除的最少字符数量,使其成为字典词汇序列。通过实例分析,详细解释了解决该问题的算法步骤。

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The Cow Lexicon
Time Limit: 2000MS Memory Limit: 65536K
Total Submissions: 6548 Accepted: 3021

Description

Few know that the cows have their own dictionary with W (1 ≤ W ≤ 600) words, each containing no more 25 of the characters 'a'..'z'. Their cowmunication system, based on mooing, is not very accurate; sometimes they hear words that do not make any sense. For instance, Bessie once received a message that said "browndcodw". As it turns out, the intended message was "browncow" and the two letter "d"s were noise from other parts of the barnyard.

The cows want you to help them decipher a received message (also containing only characters in the range 'a'..'z') of length L (2 ≤ L ≤ 300) characters that is a bit garbled. In particular, they know that the message has some extra letters, and they want you to determine the smallest number of letters that must be removed to make the message a sequence of words from the dictionary.

Input

Line 1: Two space-separated integers, respectively: W and L
Line 2: L characters (followed by a newline, of course): the received message
Lines 3.. W+2: The cows' dictionary, one word per line

Output

Line 1: a single integer that is the smallest number of characters that need to be removed to make the message a sequence of dictionary words.

Sample Input

6 10
browndcodw
cow
milk
white
black
brown
farmer

Sample Output

2

Source

做这个题目的时候是一点思路没有,感觉用dp但是不会搞,所以直接看了一下解题报告
#include <iostream>
#include <string.h>
using namespace std;
int dp[400];
string s1[610];
string s2;
int min1;
int main()
{
    int i,j,n,m,s,t;
    int len,l,x,y;
    cin>>n>>len;
    cin>>s2;
    for(i=1; i<=n; i++)
    {
        cin>>s1[i];
    }
    dp[len]=0;
    for(i=len-1; i>=0; i--)
    {
        dp[i]=dp[i+1]+1;
        for(j=1; j<=n; j++)
        {
            l=s1[j].size();
            if(l<=(len-i)&&s2[i]==s1[j][0])
            {
                for(x=i,y=0; x<=len-1; x++)
                {
                    if(s2[x]==s1[j][y])
                    {
                        y++;
                    }
                    if(y==l)
                    {
                        if(dp[i]>(dp[x+1]+(x+1)-i-l))
                        {
                            dp[i]=(dp[x+1]+(x+1)-i-l);
                        }
                    }
                }
            }
        }
    }
    cout<<dp[0]<<endl;
    return 0;
}

内容概要:本文详细探讨了基于MATLAB/SIMULINK的多载波无线通信系统仿真及性能分析,重点研究了以OFDM为代表的多载波技术。文章首先介绍了OFDM的基本原理和系统组成,随后通过仿真平台分析了不同调制方式的抗干扰性能、信道估计算法对系统性能的影响以及同步技术的实现与分析。文中提供了详细的MATLAB代码实现,涵盖OFDM系统的基本仿真、信道估计算法比较、同步算法实现和不同调制方式的性能比较。此外,还讨论了信道特征、OFDM关键技术、信道估计、同步技术和系统级仿真架构,并提出了未来的改进方向,如深度学习增强、混合波形设计和硬件加速方案。; 适合人群:具备无线通信基础知识,尤其是对OFDM技术有一定了解的研究人员和技术人员;从事无线通信系统设计与开发的工程师;高校通信工程专业的高年级本科生和研究生。; 使用场景及目标:①理解OFDM系统的工作原理及其在多径信道环境下的性能表现;②掌握MATLAB/SIMULINK在无线通信系统仿真中的应用;③评估不同调制方式、信道估计算法和同步算法的优劣;④为实际OFDM系统的设计和优化提供理论依据和技术支持。; 其他说明:本文不仅提供了详细的理论分析,还附带了大量的MATLAB代码示例,便于读者动手实践。建议读者在学习过程中结合代码进行调试和实验,以加深对OFDM技术的理解。此外,文中还涉及了一些最新的研究方向和技术趋势,如AI增强和毫米波通信,为读者提供了更广阔的视野。
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