# User Reference:FFTFilter

## Contents

## Function

The FFTFilter applies a short-term Fast Fourier Transformation (FFT) to selected channels of its input signal, resulting in a time series of frequency spectra. The computed spectra may be displayed in visualization windows.

Typically, the FFTFilter is used for spectral estimation and demodulation, instead of the ARFilter.

## Parameters

### FFTOutputSignal

Depending on configuration, the FFT filter's output signal will be the computed spectrum, or the unchanged input. Possible values are

- 0 for input connect-through--

this option allows using the FFTFilter for visualization purposes. - 1 for power spectrum--

as with the ARFilter, the output signal's elements will correspond to frequency bins. - 2 for complex amplitudes--

the output will be complex fourier coefficients in halfcomplex format, with the spectrum's imaginary part appended to the real part.

### FFTInputChannels

A list of input channels for which the FFT is computed. When FFTOutputSignal is set to other than 0, FFTInputChannels list entries determine the correspondence between input and output channels.

### FFTWindowLength

The length of the input data window over which the FFT is computed, given as a time value in seconds, or the number of signal blocks as in the following examples:

1.34s 500ms 5

The FFT will be computed once per data block. If the length of the input data window exceeds that of a data block, FFT windows will overlap. If the data window is shorter than a data block, only the most recent samples will enter into the FFT.

### FFTWindow

Selects the type of sidelobe suppression window. Possible values are

- 1 for a Hamming window,
- 2 for a Hann window,
- 3 for a Blackman window.

### VisualizeFFT

A nonzero value selects visualization of the FFT-computed power spectrum. Independently of the FFTOutputSignal parameter's value, it is always the power spectrum that is visualized.

## States

None.