1. 程式人生 > >數字訊號產生之貝努裡高斯分佈的隨機數

數字訊號產生之貝努裡高斯分佈的隨機數

uniform.h

#pragma once

class uniform
{
private:
 double a, b, generate_num;
 int * seed;
 int s;
 int M, N, i, j;

public:
 uniform()
 {
  M = 1048576;
  N = 2045;
 }
 void generate();
 double random_number(double, double, int *);
};

double uniform::random_number(double a, double b, int * seed)
{
 (*seed) = N * (*seed) + 1;
 (*seed) = (*seed) - ((*seed) / M) * M;
 generate_num = static_cast<double>((*seed)) / M;
 generate_num = a + (b - a) * generate_num;
 return (generate_num);
}

gauss.h

#pragma once
#include "uniform.h"

uniform unif_num;

class gauss
{
private:
 double mean, sigma, x, y, generate_num;
 int s;
 int * seed;
 int i, j, m;

public:
 gauss() {}
 void generate();
 double random_number(double, double, int *);
};

double gauss::random_number(double mean, double sigma, int * seed)
{
 x = 0;
 for (m = 0; m < 12; m++)
 {
  x += unif_num.random_number(0.0, 1.0, seed);
 }
 x = x - 6.0;
 y = mean + x * sigma;
 return (y);
}

bernoulli_gauss.h

#pragma once
#include "gauss.h"

class bernoulli_gauss
{
private:
 double p, mean, sigma, u, x, generate_num;
 int * seed;
 int s, i, j;

public:
 bernoulli_gauss() {}
 void generate();
 double random_number(double, double, double, int *);
};

double bernoulli_gauss::random_number(double p, double mean, double sigma, int * seed)
{
 uniform unif_num;
 gauss gau_num;
 u = unif_num.random_number(0.0, 1.0, seed);
 if (u <= p)
  x = gau_num.random_number(mean, sigma, seed);
 else
  x = 0.0;
 return (x);
}

bernoulli_gauss.cpp

//產生50個引數p = 0.4、mean = 0、sigma = 1的貝努裡_高斯分佈的隨機數
#include <iostream>
#include <iomanip>
#include "bernoulli_gauss.h"

using namespace std;

void main()
{
 bernoulli_gauss solution;
 solution.generate();
}

void bernoulli_gauss::generate()
{
 cout << "輸入貝努裡_高斯分佈的引數p:";
 cin >> p;
 cout << "輸入貝努裡_高斯分佈的均值:";
 cin >> mean;
 cout << "輸入貝努裡_高斯分佈的均方差:";
 cin >> sigma;
 cout << "輸入隨機數的種子:";
 cin >> s;
 cout << "生成隨機數的結果為:" << endl;
 for (i = 0; i < 10; i++)
 {
  for (j = 0; j < 5; j++)
  {
   generate_num = random_number(p, mean, sigma, &s);
   cout << setw(10) << generate_num;
  }
  cout << endl;
 }
}