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我有一个输入信号，我计算了它的FFT。之后，我只需要在频率带宽上计算其均方根值，而不是针对所有频谱。获得每个频率的RMS
我使用Parseval定理求解了整个频谱的RMS计算，但是如何计算这种RMS“选择性”？我已经正确地计算了索引以获得三个感兴趣的频率（F0，FC，F1），但是当将RMS应用于该频带时，似乎Parseval的定理不是完整的。
我收到一个独特的10 KHz频率，从FFT总频谱的RMS是正确的，但其RMS选择性在10 KHz频率给我一个错误的结果（-0.4V从RMS正确的一个），应该给我几乎相同因为我在频谱中只有一个频率。在这里，您可以看到我的RMS选择性计算：
public static double RMSSelectiveCalculation(double[] trama, double samplingFreq, double F0, double Fc, double F1)
{
//Frequency of interest
double fs = samplingFreq; // Sampling frequency
double t1 = 1/fs; // Sample time
int l = trama.Length; // Length of signal
double rmsSelective = 0;
double ParsevalB = 0;
double scalingFactor = fs;
double dt = 1/fs;
// We just use half of the data as the other half is simetric. The middle is found in NFFT/2 + 1
int nFFT = (int)Math.Pow(2, NextPow2(l));
double df = fs/nFFT;
if (nFFT > 655600)
{ }
// Create complex array for FFT transformation. Use 0s for imaginary part
Complex[] samples = new Complex[nFFT];
Complex[] reverseSamples = new Complex[nFFT];
double[] frecuencies = new double[nFFT];
for (int i = 0; i < nFFT; i++)
{
frecuencies[i] = i * (fs/nFFT);
if (i >= trama.Length)
{
samples[i] = new MathNet.Numerics.Complex(0, 0);
}
else
{
samples[i] = new MathNet.Numerics.Complex(trama[i], 0);
}
}
ComplexFourierTransformation fft = new ComplexFourierTransformation(TransformationConvention.Matlab);
fft.TransformForward(samples);
ComplexVector s = new ComplexVector(samples);
//The indexes will get the index of each frecuency
int f0Index, fcIndex, f1Index;
double k = nFFT/fs;
f0Index = (int)Math.Floor(k * F0);
fcIndex = (int)Math.Floor(k * Fc);
f1Index = (int)Math.Ceiling(k * F1);
for (int i = f0Index; i <= f1Index; i++)
{
ParsevalB += Math.Pow(Math.Abs(s[i].Modulus/scalingFactor), 2.0);
}
ParsevalB = ParsevalB * df;
double ownSF = fs/l; //This is a own scale factor used to take the square root after
rmsSelective = Math.Sqrt(ParsevalB * ownSF);
samples = null;
s = null;
return rmsSelective;
}
你以前没有问过这个问题吗？ [从FFT获取RMS]（http://stackoverflow.com/questions/43452138/getting-rms-from-fft）和[从FFT获取RMS]（http://stackoverflow.com/questions/43363860/get-rms -from-fft）？ –