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法律研究C++ 對給定的複雜 2D 陣列進行就地 2D FFT
快速傅立葉變換 (FFT) 是一個計算離散傅立葉變換 (DFT) 及其逆變換的演算法。基本上，傅立葉分析將時間（或空間）轉換為頻率，反之亦然。FFT 透過將 DFT 矩陣分解為稀疏（大多為零）因子的乘積來快速計算變換。
演算法
Begin Declare the size of the array Take the elements of the array Declare three arrays Initialize height =size of array and width=size of array Create two outer loops to iterate on output data Create two outer loops to iterate on input data Compute real, img and amp. End
示例程式碼
#include <iostream>
#include <math.h>
using namespace std;
#define PI 3.14159265
int n;
int main(int argc, char **argv) {
cout << "Enter the size: ";
cin >> n;
double Data[n][n];
cout << "Enter the 2D elements ";
for (int i = 0; i < n; i++)
for (int j = 0; j < n; j++)
cin >> Data[i][j];
double realOut[n][n];
double imgOut[n][n];
double ampOut[n][n];
int height = n;
int width = n;
for (int yWave = 0; yWave < height; yWave++) {
for (int xWave = 0; xWave < width; xWave++) {
for (int ySpace = 0; ySpace < height; ySpace++) {
for (int xSpace = 0; xSpace < width; xSpace++) {
realOut[yWave][xWave] += (Data[ySpace][xSpace] * cos(2 *
PI * ((1.0 * xWave * xSpace / width) + (1.0 * yWave * ySpace /
height)))) / sqrt(width * height);
imgOut[yWave][xWave] -= (Data[ySpace][xSpace] * sin(2 * PI
* ((1.0 * xWave * xSpace / width) + (1.0 * yWave * ySpace / height)))) /
sqrt( width * height);
ampOut[yWave][xWave] = sqrt(
realOut[yWave][xWave] * realOut[yWave][xWave] +
imgOut[yWave][xWave] * imgOut[yWave][xWave]);
}
cout << realOut[yWave][xWave] << " + " <<
imgOut[yWave][xWave] << " i (" << ampOut[yWave][xWave] << ")\n";
}
}
}
}輸出
Enter the size: 2 Enter the 2D elements 4 5 6 7 4.5 + 6.60611e-310 i (4.5) 11 + 6.60611e-310 i (11) -0.5 + -8.97448e-09 i (0.5) -1 + -2.15388e-08 i (1) 4.5 + 6.60611e-310 i (4.5) -2 + -2.33337e-08 i (2) -0.5 + -8.97448e-09 i (0.5) 0 + 5.38469e-09 i (5.38469e-09)
更新於：30-Jul-2019
731 次瀏覽
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