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Signal Analysis for .NET
FastThe FFT implementation in this product is much faster than some implementations found in more expensive commercial products like the $395 TransformNET software from Windale Technologies:
Specifically, our implementation maintains optimal O(n log n) complexity for all n, allowing you to transform large data sets without having to worry about performance. Easy to useA simple 5-point transform can be calculated in only a few lines of code, as the following self-contained C# program demonstrates: using FlyingFrog;
namespace CSFFTTest
{
class Program
{
static void print(Complex[] a)
{
foreach(Complex z in a) System.Console.Write(Complex.Chop(z) + " ");
System.Console.Write("\n");
}
static void Main(string[] args)
{
Complex[] a = new Complex[5];
a[1] = 1;
a[4] = -1;
System.Console.Write("a = ");
print(a);
FFT.fourier(a);
System.Console.Write("fourier(a) = ");
print(a);
FFT.ifourier(a);
System.Console.Write("ifourier(fourier(a)) = ");
print(a);
}
}
}
This program produces the following output: a = 0 1 0 0 -1 fourier(a) = 0 1.90211303259031i 1.17557050458495i -1.17557050458495i -1.90211303259031i ifourier(fourier(a)) = 0 5 0 0 -5 Our Signal Analysis for .NET library allows you to compute Fourier transforms faster, easier and cheaper than before!
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