Table Of Contents

FFT (Multirate Dataflow)

Last Modified: September 10, 2016

Performs a Discrete Fourier Transform (DFT) on complex input data using an optimized Fast Fourier Transform (FFT) algorithm.

connector_pane_image
datatype_icon

input

Input values to transform.

On the host, the default data type of this input is complex double-precision floating-point.

datatype_icon

output

Result of the transform.

On the host, the default data type of this input is complex double-precision floating-point.

If you configure the node to add a cyclic prefix of length N, the first N samples are prefix values.

FFT Configuration

You can configure the FFT to perform forward or inverse transforms on power-of-two transform lengths, also known as point sizes. You can also configure the FFT to apply the same transform to up to 4 channels in parallel, with or without shifting the DC component to center and with or without applying a cyclic prefix.

spd-note-note
Note  

If you connect any floating-point wires to the FFT, LabVIEW disables the Design Clock Rate, Throughput, and Range because the FFT runs only a model of the transform algorithm. To configure these options, you must implement the FFT using fixed-point data.

Fixed-Point Implementation

If you do not connect any floating-point wires to the FFT, the FFT automatically selects an optimized fixed-point implementation. The fixed-point implementation of the FFT supports complex inputs between 8 and 32 bits wide and automatically expands output width to accommodate internal bit growth.

The fixed-point FFT attempts to auto-select the least resource-intensive architecture that meets or exceeds the throughput goal you configure.

Where This Node Can Run:

Desktop OS: Windows

FPGA: All devices


Recently Viewed Topics