The fast Fourier transform (FFT) is an algorithm for the efficient calculation of the discrete Fourier transform (DFT). It can be used to decompose a discrete-time signal into its frequency components and thus analyze it.
With the calculator, the Fourier transform can be applied to any measured values or alternatively to a function with equidistant samples. The number of samples must be a power of two for the FFT.
Real part
Imaginary part
Amount
Phase
f(x)=
Function | Description |
---|---|
sin(x) | Sine of x |
cos(x) | Cosine of x |
tan(x) | Tangent of x |
asin(x) | arcsine |
acos(x) | arccosine of x |
atan(x) | arctangent of x |
atan2(y, x) | Returns the arctangent of the quotient of its arguments. |
cosh(x) | Hyperbolic cosine of x |
sinh(x) | Hyperbolic sine of x |
pow(a, b) | Power ab |
sqrt(x) | Square root of x |
exp(x) | e-function |
log(x), ln(x) | Natural logarithm |
log(x, b) | Logarithm to base b |
log2(x), lb(x) | Logarithm to base 2 |
log10(x), ld(x) | Logarithm to base 10 |
An alternative input is possible by loading the data from a file. The sampled values must be separated by comma, space or semicolon. At the end there must be a semicolon as termination.
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Here is a list of of further useful sites:
Index Calculator for Fourier series expansion Curve fitting for: linear line, power function, polynomial, normal distribution Newton Interpolation Horners Method Trigonometric calculations Taylor series calculator Normal Distribution Plot NxN Gauss method Derivation rules ODE first order