多个文件的内存分配错误"在抛出 'std :: bad_alloc' what ()： std ：： bad_alloc 的实例后终止调用" [C++]

我正在为一个数字语音信号处理项目使用分类器算法。这个算法是为了接收单个矢量中的所有音频信号来进行处理而开发的，但我遇到了问题，因为我正在处理的文件数量非常大，并且正在产生错误"；在抛出"std:：bad_alloc"what((：std:：bad_alloc"的实例后调用terminate；。我想知道是否可以在不超过可用内存空间的情况下，对读取文件并将其存储在向量中的代码进行任何更改。

读取文件的代码：

string filename;
filename="C:\Users\marcu\Desktop\TCC\Arquivos_10780\Arquivos_DFT_TXT_512\PA_D_00";
std::vector<double> c;
for(int j=1; j<=5400; j++)
{
stringstream ss;
ss << filename << setw(5) << setfill('0') << j << "_bonafide_DFT.txt";
std::ifstream f;
f.open(ss.str().c_str());
if (f.is_open())
{
double num;
while (f >> num)
c.push_back(num);
f.close();
}
else
{
f.close();
continue;
}
}
for(int j=5401; j<=29700; j++)
{
stringstream ss;
ss << filename << setw(5) << setfill('0') << j << "_spoof_DFT.txt";
std::ifstream f;
f.open(ss.str().c_str());
if (f.is_open())
{
double num;
while (f >> num)
c.push_back(num);
f.close();
}
else
{
f.close();
continue;
}
}

完整代码：

#include<stdio.h>
#include<math.h>
#include<string.h>
#include<iostream>
#include<fstream>
#include<string>
#include<vector>
#include<stdlib.h>
#include<iomanip>
#include<sstream>
using namespace std;
double mean_similarities(double**,int,int);//vectors, number of vectors, their dimension
int main()
{
const int number_of_classes=2;
int number_of_feature_vectors_in_class[number_of_classes];
number_of_feature_vectors_in_class[0]=2700;
number_of_feature_vectors_in_class[1]=8080;
const int dimension_of_each_feature_vector=512;
////////////////////////////////////////////////////////////////////////////////////////////
/*
Example: 3 classes and 4 vectors of dimension 2 in each class
{{0.90,0.12},{0.88,0.14},{0.88,0.13},{0.89,0.11}}   //0.88---0.90 ; 0.11---0.14
{{0.55,0.53},{0.53,0.55},{0.54,0.54},{0.56,0.54}}   //0.53---0.56 ; 0.53---0.55
{{0.10,0.88},{0.11,0.86},{0.12,0.87},{0.11,0.88}}   //0.10---0.12 ; 0.86---0.88  
double c[]={ 
0.90,0.12,0.88,0.14,0.88,0.13,0.89,0.11,
0.55,0.53,0.53,0.55,0.54,0.54,0.56,0.54,
0.10,0.88,0.11,0.86,0.12,0.87,0.11,0.88
//all vectors in class C_1, followed by all vectors in C_2, ...., followed by all in C_n
};
*/
////////////////////////////////////////////////////////////////////////////////////////////
string filename;
filename="C:\Users\marcu\Desktop\TCC\Arquivos_10780\Arquivos_DFT_TXT_512\PA_D_00";
std::vector<double> c;
for(int j=1; j<=5400; j++)
{
stringstream ss;
ss << filename << setw(5) << setfill('0') << j << "_bonafide_DFT.txt";
std::ifstream f;
f.open(ss.str().c_str());
if (f.is_open())
{
double num;
while (f >> num)
c.push_back(num);
f.close();
}
else
{
f.close();
continue;
}
}
for(int j=5401; j<=29700; j++)
{
stringstream ss;
ss << filename << setw(5) << setfill('0') << j << "_spoof_DFT.txt";
std::ifstream f;
f.open(ss.str().c_str());
if (f.is_open())
{
double num;
while (f >> num)
c.push_back(num);
f.close();
}
else
{
f.close();
continue;
}
}
////////////////////////////////////////////////////////////////////////////////////////////
//edit whatever you need, according to the feature vectors of your problem, ABOVE this line.
//Do NOT change anything BELOW this line !!!!!
////////////////////////////////////////////////////////////////////////////////////////////
double*** C=new double**[number_of_classes];
for(int i=0; i<number_of_classes; i++)
C[i]=new double*[number_of_feature_vectors_in_class[i]];
for(int i=0; i<number_of_classes; i++)
for(int j=0; j<number_of_feature_vectors_in_class[i]; j++)
C[i][j]=new double[dimension_of_each_feature_vector];
int l=0;
for(int i=0; i<number_of_classes; i++)
for(int j=0; j<number_of_feature_vectors_in_class[i]; j++)
for(int k=0; k<dimension_of_each_feature_vector; k++)
{
C[i][j][k]=c[l];
l++;
}
//Debug info only
//for(int i=0;i<number_of_classes;i++)
//  for(int j=0;j<number_of_feature_vectors_in_class[i];j++)
//      for(int k=0;k<dimension_of_each_feature_vector;k++)
//          printf("nclass %d vector %d element %d is %.3f",i,j,k,C[i][j][k]);
//getchar();
double Y[number_of_classes];
for(int i=0; i<number_of_classes; i++)
Y[i]=mean_similarities(C[i],number_of_feature_vectors_in_class[i],dimension_of_each_feature_vector);
double alpha=Y[0];
for(int i=1; i<number_of_classes; i++)
if(Y[i]<alpha)
alpha=Y[i];
printf("nALPHA: %.3f",alpha);
double** smallest_range_vector_for_class=new double*[number_of_classes];
for(int i=0; i<number_of_classes; i++)
smallest_range_vector_for_class[i]=new double[dimension_of_each_feature_vector];
for(int i=0; i<number_of_classes; i++)
for(int k=0; k<dimension_of_each_feature_vector; k++)
smallest_range_vector_for_class[i][k]=C[i][0][k];
for(int i=0; i<number_of_classes; i++)
for(int j=1; j<number_of_feature_vectors_in_class[i]; j++)
for(int k=0; k<dimension_of_each_feature_vector; k++)
if(C[i][j][k]<smallest_range_vector_for_class[i][k])
smallest_range_vector_for_class[i][k]=C[i][j][k];
//Debug info only
//for(int i=0;i<number_of_classes;i++)
//  for(int k=0;k<dimension_of_each_feature_vector;k++)
//          printf("nclass %d smallest component %d is %.3f",i,k,smallest_range_vector_for_class[i][k]);
double** largest_range_vector_for_class=new double*[number_of_classes];
for(int i=0; i<number_of_classes; i++)
largest_range_vector_for_class[i]=new double[dimension_of_each_feature_vector];
for(int i=0; i<number_of_classes; i++)
for(int k=0; k<dimension_of_each_feature_vector; k++)
largest_range_vector_for_class[i][k]=C[i][0][k];
for(int i=0; i<number_of_classes; i++)
for(int j=1; j<number_of_feature_vectors_in_class[i]; j++)
for(int k=0; k<dimension_of_each_feature_vector; k++)
if(C[i][j][k]>largest_range_vector_for_class[i][k])
largest_range_vector_for_class[i][k]=C[i][j][k];
//Debug info only
//for(int i=0;i<number_of_classes;i++)
//  for(int k=0;k<dimension_of_each_feature_vector;k++)
//          printf("nclass %d largest component %d is %.3f",i,k,largest_range_vector_for_class[i][k]);
int R=0;
int F=0;
for(int ia=0; ia<number_of_classes; ia++)
for(int ib=0; ib<number_of_classes; ib++)
for(int j=0; j<number_of_feature_vectors_in_class[ib]; j++)
for(int k=0; k<dimension_of_each_feature_vector; k++)
{
if(ib!=ia)
{
if((C[ib][j][k]>smallest_range_vector_for_class[ia][k])&&(C[ib][j][k]<largest_range_vector_for_class[ia][k]))
R++;
F++;
}
}
double beta=((double)(R))/((double)(F));
printf("nBETA: %.3f",beta);
printf("nP=(G1,G2)=(%.3f,%.3f)",alpha-beta,alpha+beta-1);
printf("nDistance from P to (1,0): %.3f",sqrt(pow((alpha-beta)-1,2)+pow(alpha+beta-1,2)));
printf("nn");
}
/////////////////////////////////////////////
////////////////////////////////////////////
double mean_similarities(double** v,int n, int t)
{
double largest;
double smallest;
double* s=new double[t];
for(int i=0; i<t; i++)
{
smallest=1;
largest=0;
for(int j=0; j<n; j++)
{
if(v[j][i]>largest)
largest=v[j][i];
if(v[j][i]<smallest)
smallest=v[j][i];
}
s[i]=1-(largest-smallest);
}
double m=0;
for(int i=0; i<t; i++)
m+=s[i];
m/=((double)(t));
return(m);
}

PS：为了找到最好的分类器结果，我需要将文件大小(每个文件的信息量(更改为越来越大的值。一开始有512个点，但每次执行时我都会将这个值加倍，直到达到8192，但当我尝试使用16384时，代码会崩溃。我正在处理10780个文件，每个文件都有相同的尺寸，我在检查结果时会增加它。