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Front-end 的查询结果
源码 数据结构实验
#include <iostream>
#include <stdio.head>
#include <stdlib.head>
#include <string.head>
#define ElemType int
#define max 100
using namespace std;
typedef struct node1
{
ElemType data;
struct node1 *next;
}Node1,*LinkList;//链栈
typedef struct
{
ElemType *base;
int top;
}SqStack;// ...
其他 有限差分法
function&nbsp;[alpha,N,U]=youxianchafen2(r1,r2,up,under,num,deta)&nbsp;&nbsp;
&nbsp;&nbsp;
%[alpha,N,U]=youxianchafen2(a,r1,r2,up,under,num,deta)&nbsp;&nbsp;
%该函数用有限差分法求解有两种介质的正方形区域的二维拉普拉斯方程的数值解&nbsp;&nbsp;
%函数返回迭代因子、迭代次数 ...
源码 成绩查询系统
#include<stdio.h>
#include<string.h>
#include<stdlib.h>
#define N 100
int iNumOfStu=0;
struct score
&nbsp;&nbsp;{
&nbsp;&nbsp;float math;
&nbsp;&nbsp;float english;
&nbsp;&nbsp;float computer;
&nbsp;&nbsp;};
struct student
&nbsp;&nbsp;{
&nbsp;&nbsp;int number ...
源码 学生成绩guanli
#include<stdio.h>
#include<string.h>
#include<stdlib.h>
#define N 100
int iNumOfStu=0;
struct score
&nbsp;&nbsp;{
&nbsp;&nbsp;float math;
&nbsp;&nbsp;float english;
&nbsp;&nbsp;float computer;
&nbsp;&nbsp;};
struct student
&nbsp;&nbsp;{
&nbsp;&nbsp;int number ...
源码 能频值算法
nx=length(x(:));
if nargin<2 || isempty(win)
win=nx;
end
if nargin<4 || isempty(m)
m='';
end
nwin=length(win);
if nwin == 1
lw = win;
w = ones(1,lw);
else
lw = nwin;
w = win(:)';
end
技术资料 多元散射校正MSC
function [R,k,b] = msc(A)
% 多元散射校正
% 输入待处理矩阵,通过多元散射校正,求得校正后的矩阵
%% 获得矩阵行列数
[m,n] = size(A);
%% 求平均光谱
M = mean(A,2);
%% 利用最小二乘法求每一列的斜率k和截距b
for i = 1:n
a = polyfit(M,A(:,i),1);
if i == 1
k = a(1);
b = a(2);
...
源码 源代码LIBRARY IEEE USE IEEE
通用寄存器的部分代码 LIBRARY IEEE USE IEEE.STD_LOGIC_1164.ALL ENTITY traffic IS PORT(clk,sm,sb:IN bit mr,my,mg,br,by,bg:OUT bit ) END traffic
源码 matlab神经网络算法通信信号调制识别
%========================开始提取加噪信号的各类特征值================================
for n=1:1:50;
&nbsp; &nbsp; m=n*Ns;
&nbsp; &nbsp; x=(n-1)*Ns;
for i=x+1:m;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; %提取加噪信号'signal_with_noise=y+noise'的前256个元素,抽取50次
&nbsp; &nbsp; y0(i)=signal_with_noise(i); ...
源码 matlab神经网络算法通信信号调制识别y
%========================开始提取加噪信号的各类特征值================================
for n=1:1:50;
&nbsp; &nbsp; m=n*Ns;
&nbsp; &nbsp; x=(n-1)*Ns;
for i=x+1:m;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; %提取加噪信号'signal_with_noise=y+noise'的前256个元素,抽取50次
&nbsp; &nbsp; y0(i)=signal_with_noise(i); ...