/// <summary>
/// Fast convolution via FFT for general complex-valued case
/// </summary>
/// <param name="signal"></param>
/// <param name="kernel"></param>
/// <returns></returns>
public ComplexDiscreteSignal Convolve(ComplexDiscreteSignal signal, ComplexDiscreteSignal kernel)
{
var length = signal.Length + kernel.Length - 1;
var fftSize = MathUtils.NextPowerOfTwo(length);
var fft = new Fft64(fftSize);
signal = signal.ZeroPadded(fftSize);
kernel = kernel.ZeroPadded(fftSize);
// 1) do FFT of both signals
fft.Direct(signal.Real, signal.Imag);
fft.Direct(kernel.Real, kernel.Imag);
// 2) do complex multiplication of spectra
var spectrum = signal.Multiply(kernel);
// 3) do inverse FFT of resulting spectrum
fft.Inverse(spectrum.Real, spectrum.Imag);
// 3a) normalize
for (var i = 0; i < spectrum.Length; i++)
{
spectrum.Real[i] /= fftSize;
spectrum.Imag[i] /= fftSize;
}
// 4) return resulting meaningful part of the signal (truncate size to N + M - 1)
return(new ComplexDiscreteSignal(signal.SamplingRate, spectrum.Real, spectrum.Imag).First(length));
}
/// <summary>
/// Fast deconvolution via FFT for general complex-valued case.
///
/// NOTE!
///
/// Deconvolution is an experimental feature.
/// It's problematic due to division by zero.
///
/// </summary>
/// <param name="signal"></param>
/// <param name="kernel"></param>
/// <param name="fftSize"></param>
/// <returns></returns>
public ComplexDiscreteSignal Deconvolve(ComplexDiscreteSignal signal, ComplexDiscreteSignal kernel, int fftSize = 0)
{
// first, try to divide polynomials
var div = MathUtils.DividePolynomial(signal.Real.Zip(signal.Imag, (r, i) => new Complex(r, i)).ToArray(),
kernel.Real.Zip(kernel.Imag, (r, i) => new Complex(r, i)).ToArray());
var quotient = div[0];
var remainder = div[1];
if (remainder.All(d => Math.Abs(d.Real) < 1e-10) &&
remainder.All(d => Math.Abs(d.Imaginary) < 1e-10))
{
return(new ComplexDiscreteSignal(signal.SamplingRate,
quotient.Select(q => q.Real),
quotient.Select(q => q.Imaginary)));
}
// ... deconvolve via FFT
var length = signal.Length - kernel.Length + 1;
if (fftSize == 0)
{
fftSize = MathUtils.NextPowerOfTwo(signal.Length);
}
var fft = new Fft64(fftSize);
signal = signal.ZeroPadded(fftSize);
kernel = kernel.ZeroPadded(fftSize);
// 1) do FFT of both signals
fft.Direct(signal.Real, signal.Imag);
fft.Direct(kernel.Real, kernel.Imag);
for (var i = 0; i < fftSize; i++)
{
signal.Real[i] += 1e-10;
signal.Imag[i] += 1e-10;
kernel.Real[i] += 1e-10;
kernel.Imag[i] += 1e-10;
}
// 2) do complex division of spectra
var spectrum = signal.Divide(kernel);
// 3) do inverse FFT of resulting spectrum
fft.Inverse(spectrum.Real, spectrum.Imag);
// 4) return resulting meaningful part of the signal (truncate to N - M + 1)
return(new ComplexDiscreteSignal(signal.SamplingRate,
spectrum.Real.FastCopyFragment(length),
spectrum.Imag.FastCopyFragment(length)));
}
/// <summary>
/// Frequency response of an FIR filter is the FT of its impulse response
/// </summary>
public override ComplexDiscreteSignal FrequencyResponse(int length = 512)
{
var real = Kernel.PadZeros(length);
var imag = new double[length];
var fft = new Fft64(length);
fft.Direct(real, imag);
return(new ComplexDiscreteSignal(1, real.Take(length / 2 + 1),
imag.Take(length / 2 + 1)));
}
/// <summary>
/// Returns the complex frequency response of a filter.
///
/// Method calculates the Frequency Response of a filter
/// by taking FFT of an impulse response (possibly truncated).
/// </summary>
/// <param name="length">Number of frequency response samples</param>
public virtual ComplexDiscreteSignal FrequencyResponse(int length = 512)
{
var real = ImpulseResponse(length);
var imag = new double[length];
var fft = new Fft64(length);
fft.Direct(real, imag);
return(new ComplexDiscreteSignal(1, real.Take(length / 2 + 1),
imag.Take(length / 2 + 1)));
}
/// <summary>
/// Evaluate frequency response
/// </summary>
/// <param name="length"></param>
/// <returns></returns>
public ComplexDiscreteSignal FrequencyResponse(int length = 512)
{
var ir = ImpulseResponse(length);
var real = ir.Length == length ? ir :
ir.Length < length?ir.PadZeros(length) :
ir.FastCopyFragment(length);
var imag = new double[length];
var fft = new Fft64(length);
fft.Direct(real, imag);
return(new ComplexDiscreteSignal(1, real.Take(length / 2 + 1),
imag.Take(length / 2 + 1)));
}
/// <summary>
/// Group delay calculated from TF coefficients
/// </summary>
public double[] GroupDelay(int fftSize = 512)
{
var cc = Operation.CrossCorrelate(new ComplexDiscreteSignal(1, Numerator),
new ComplexDiscreteSignal(1, Denominator)).Real;
var cr = Enumerable.Range(0, cc.Length)
.Zip(cc, (r, c) => r * c)
.ToArray();
var re = cc.PadZeros(fftSize);
var im = new double[fftSize];
var fft = new Fft64(fftSize);
fft.Direct(re, im);
var rre = cr.PadZeros(fftSize);
var rim = new double[fftSize];
fft.Direct(rre, rim);
var num = rre.Zip(rim, (r, i) => new Complex(r, i)).ToArray();
var den = re.Zip(im, (r, i) => new Complex(r, i)).ToArray();
var dn = Numerator.Length - 1;
var gd = new double[fftSize / 2];
for (var i = 1; i <= gd.Length; i++)
{
if (Complex.Abs(den[i]) < 1e-10)
{
num[i] = Complex.Zero;
den[i] = Complex.One;
}
var t = dn - num[i] / den[i];
gd[i - 1] = t.Real;
}
return(gd);
}
/// <summary>
/// FIR filter design using frequency sampling method
/// </summary>
/// <param name="order">Filter order</param>
/// <param name="magnitudeResponse">Magnitude response</param>
/// <param name="phaseResponse">Phase response</param>
/// <param name="window">Window</param>
/// <returns>FIR filter kernel</returns>
public static double[] Fir(int order,
double[] magnitudeResponse,
double[] phaseResponse = null,
WindowTypes window = WindowTypes.Blackman)
{
Guard.AgainstEvenNumber(order, "The order of the filter");
var fftSize = MathUtils.NextPowerOfTwo(magnitudeResponse.Length);
var real = phaseResponse == null?
magnitudeResponse.PadZeros(fftSize) :
magnitudeResponse.Zip(phaseResponse, (m, p) => m * Math.Cos(p)).ToArray();
var imag = phaseResponse == null ?
new double[fftSize] :
magnitudeResponse.Zip(phaseResponse, (m, p) => m * Math.Sin(p)).ToArray();
var fft = new Fft64(fftSize);
fft.Inverse(real, imag);
var kernel = new double[order];
var compensation = 2.0 / fftSize;
var middle = order / 2;
for (var i = 0; i <= middle; i++)
{
kernel[i] = real[middle - i] * compensation;
kernel[i + middle] = real[i] * compensation;
}
kernel.ApplyWindow(window);
return(kernel);
}
/// <summary>
/// Method for FIR filter design using window method
/// </summary>
/// <param name="order"></param>
/// <param name="magnitudeResponse"></param>
/// <param name="phaseResponse"></param>
/// <param name="window"></param>
/// <returns></returns>
public static FirFilter Fir(int order, double[] magnitudeResponse, double[] phaseResponse = null, WindowTypes window = WindowTypes.Blackman)
{
if (order % 2 == 0)
{
throw new ArgumentException("The order of a filter must be an odd number!");
}
var fftSize = MathUtils.NextPowerOfTwo(magnitudeResponse.Length);
var real = phaseResponse == null?
magnitudeResponse.PadZeros(fftSize) :
magnitudeResponse.Zip(phaseResponse, (m, p) => m * Math.Cos(p)).ToArray();
var imag = phaseResponse == null ?
new double[fftSize] :
magnitudeResponse.Zip(phaseResponse, (m, p) => m * Math.Sin(p)).ToArray();
var fft = new Fft64(fftSize);
fft.Inverse(real, imag);
var kernel = new double[order];
var compensation = 2.0 / fftSize;
var middle = order / 2;
for (var i = 0; i <= middle; i++)
{
kernel[i] = real[middle - i] * compensation;
kernel[i + middle] = real[i] * compensation;
}
kernel.ApplyWindow(window);
return(new FirFilter(kernel));
}
