User`s guide

FFT
5-179
the table of trigonometric values for speed or memory by varying the number
of table entries as summarized in the following table.
Algorithms Used for FFT Computation
Depending on whether the block input is real- or complex-valued, and whether
you want the output in linear or bit-reversed order, the block uses one or more
of the following algorithms as summarized in the next table:
•Radix-2 decimation-in-time (DIT) algorithm
•Radix-2 decimation-in-frequency (DIF) algorithm
•Half-length algorithm
•Double-signal algorithm
Example Use of Outputs in Bit-Reversed Order. The FFT block runs more quickly when it
outputs in bit-reversed order. You can often use an output in bit-reversed order
when your model also uses the IFFT block (the IFFT block allows you to
indicate whether its input is in bit-reversed or linear order). For instance, set
the FFT block to output in bit-reversed order when you want to filter or
Optimize table for
Parameter Setting
Number of Table
Entries for N-Point FFT
Memory Required
for Single-Precision
512-Point FFT
Speed 3N/4 1536 bytes
Memory N/4 + 1 516 bytes
Input Complexity Output Ordering Algorithms Used for FFT Computation
Complex Linear or
bit-reversed
Radix-2 DIT
Real Linear Radix-2 DIT in conjunction with the half-length and
double-signal algorithms when possible
Real Bit-reversed Radix-2 DIF in conjunction with the half-length and
double-signal algorithms when possible