public class FFT extends Object
Constructor and Description 

FFT() 
Modifier and Type  Method and Description 

static double[] 
autoCorrelate(double[] signal)
Compute the autocorrelation of a signal, by inverse transformation of its power spectrum.

static double[] 
autoCorrelateWithZeroPadding(double[] signal)
Compute the autocorrelation of a signal, by inverse transformation of its power spectrum.

static double[] 
computeAmplitudeSpectrum_FD(double[] fft)
From the result of the FFT (in the frequency domain), compute the absolute value for each positive frequency, i.e.

static double[] 
computeAmplitudeSpectrum(double[] signal)
Convenience method for computing the absolute amplitude spectrum of a real signal.

static double[] 
computeLogAmplitudeSpectrum_FD(double[] fft)
From the result of the FFT (in the frequency domain), compute the log amplitude for each positive frequency.

static double[] 
computeLogAmplitudeSpectrum(double[] signal)
Convenience method for computing the log amplitude spectrum of a real signal.

static double[] 
computeLogPowerSpectrum_FD(double[] fft)
From the result of the FFT, compute the log (dB) power for each positive frequency.

static double[] 
computeLogPowerSpectrum(double[] signal)
Convenience method for computing the log (dB) power spectrum of a real signal.

static double[] 
computePhaseSpectrum_FD(double[] fft)
From the result of the FFT (in the frequency domain), compute the phase spectrum for each positive frequency.

static double[] 
computePowerSpectrum_FD(double[] fft)
From the result of the FFT (in the frequency domain), compute the power for each positive frequency.

static double[] 
computePowerSpectrum(double[] signal)
Convenience method for computing the absolute power spectrum of a real signal.

static double[] 
convolve_FD(double[] signal1,
double[] fft2)
Compute the convolution of two signals, by multiplying them in the frequency domain.

static double[] 
convolve_FD(double[] signal1,
double[] fft2,
double deltaT)
Compute the convolution of two signals, by multiplying them in the frequency domain.

static double[] 
convolve(double[] signal1,
double[] signal2)
Compute the convolution of two signals, by multiplying them in the frequency domain.

static double[] 
convolve(double[] signal1,
double[] signal2,
double deltaT)
Compute the convolution of two signals, by multiplying them in the frequency domain.

static double[] 
convolveWithZeroPadding(double[] signal1,
double[] signal2)
Compute the convolution of two signals, by multipying them in the frequency domain.

static double[] 
convolveWithZeroPadding(double[] signal1,
double[] signal2,
double deltaT)
Compute the convolution of two signals, by multipying them in the frequency domain.

static double[] 
correlate(double[] signal1,
double[] signal2)
Compute the correlation of two signals, by multiplying the transform of signal2 with the conjugate complex of the transform
of signal1, in the frequency domain.

static double[] 
correlateWithZeroPadding(double[] signal1,
double[] signal2)
Compute the correlation of two signals, by multipying them in the frequency domain.

static void 
main(String[] args) 
static void 
realTransform(double[] data,
boolean inverse)
Calculates the Fourier transform of a set of n realvalued data points.

static void 
transform(double[] realAndImag,
boolean inverse)
Carry out the FFT or inverse FFT, and return the result in the same arrays given as parameters.

static void 
transform(double[] real,
double[] imag,
boolean inverse)
Carry out the FFT or inverse FFT, and return the result in the same arrays given as parameters.

public static double[] computeLogPowerSpectrum(double[] signal)
signal
 the real signal for which to compute the power spectrum.public static double[] computeLogPowerSpectrum_FD(double[] fft)
fft
 the array of real and imag parts of the complex number array, fft[0] = real[0], fft[1] = real[N/2], fft[2*i] =
real[i], fft[2*i+1] = imag[i] for 1≤i<N/2public static double[] computePowerSpectrum(double[] signal)
signal
 the real signal for which to compute the power spectrum.public static double[] computePowerSpectrum_FD(double[] fft)
fft
 the array of real and imag parts of the complex number array, fft[0] = real[0], fft[1] = real[N/2], fft[2*i] =
real[i], fft[2*i+1] = imag[i] for 1≤i<N/2public static double[] computeLogAmplitudeSpectrum(double[] signal)
signal
 the real signal for which to compute the power spectrum.public static double[] computeLogAmplitudeSpectrum_FD(double[] fft)
fft
 the array of real and imag parts of the complex number array, fft[0] = real[0], fft[1] = real[N/2], fft[2*i] =
real[i], fft[2*i+1] = imag[i] for 1≤i<N/2public static double[] computeAmplitudeSpectrum(double[] signal)
signal
 the real signal for which to compute the power spectrum.public static double[] computeAmplitudeSpectrum_FD(double[] fft)
fft
 the array of real and imag parts of the complex number array, fft[0] = real[0], fft[1] = real[N/2], fft[2*i] =
real[i], fft[2*i+1] = imag[i] for 1≤i<N/2public static double[] computePhaseSpectrum_FD(double[] fft)
fft
 the array of real and imag parts of the complex number array, fft[0] = real[0], fft[1] = real[N/2], fft[2*i] =
real[i], fft[2*i+1] = imag[i] for 1≤i<N/2public static void transform(double[] real, double[] imag, boolean inverse)
real
 in "forward" FFT: as input=the timedomain signal to transform, as output=the real part of the complex
frequencies; in inverse FFT: as input=the real part of the complex frequencies, as output= the timedomain
signal.imag
 in "forward" FFT: as input=an empty array, as output=the imaginary part of the complex frequencies; in inverse
FFT: as input=the imaginary part of the complex frequencies, as output= not used.inverse
 whether to calculate the FFT or the inverse FFT.public static void transform(double[] realAndImag, boolean inverse)
realAndImag
 the array of complex numbers to transforminverse
 whether to calculate the FFT or the inverse FFT.public static void realTransform(double[] data, boolean inverse)
data
 datainverse
 inversepublic static double[] convolveWithZeroPadding(double[] signal1, double[] signal2, double deltaT)
signal1
 signal 1signal2
 signal 2deltaT
 , the time difference between two samples (= 1/samplingrate)public static double[] convolveWithZeroPadding(double[] signal1, double[] signal2)
signal1
 signal 1signal2
 signal 2public static double[] convolve(double[] signal1, double[] signal2, double deltaT)
signal1
 signal 1signal2
 signal 2deltaT
 , the time difference between two samples (= 1/samplingrate)IllegalArgumentException
 if the two input signals do not have the same length.public static double[] convolve(double[] signal1, double[] signal2)
signal1
 signal 1signal2
 signal 2IllegalArgumentException
 if the two input signals do not have the same length.public static double[] convolve_FD(double[] signal1, double[] fft2, double deltaT)
signal1
 the first input signal, in the time domainfft2
 the complex transform of the second signal, in the frequency domain fft[0] = real[0], fft[1] = real[N/2],
fft[2*i] = real[i], fft[2*i+1] = imag[i] for 1≤i<N/2deltaT
 , the time difference between two samples (= 1/samplingrate)IllegalArgumentException
 if the two input signals do not have the same length.public static double[] convolve_FD(double[] signal1, double[] fft2)
signal1
 the first input signal, in the time domainfft2
 the complex transform of the second signal, in the frequency domain fft[0] = real[0], fft[1] = real[N/2],
fft[2*i] = real[i], fft[2*i+1] = imag[i] for 1≤i<N/2IllegalArgumentException
 if the two input signals do not have the same length.public static double[] correlateWithZeroPadding(double[] signal1, double[] signal2)
signal1
 signal 1signal2
 signal 2public static double[] correlate(double[] signal1, double[] signal2)
signal1
 signal 1signal2
 signal 2IllegalArgumentException
 if the two input signals do not have the same length.public static double[] autoCorrelate(double[] signal)
signal
 signalpublic static double[] autoCorrelateWithZeroPadding(double[] signal)
signal
 signalCopyright © 2000–2018 DFKI GmbH. All rights reserved.