Figure Properties - SERC

2fftw
Purpose Interface to the FFTW library run-time algorithm for tuning fast Fourier
transform (FFT) computations
Syntax fftw('planner', method)
method = fftw('planner')
str = fftw('wisdom')
fftw('wisdom', str)
fftw('wisdom', '')
fftw('wisdom', [])
Description fftw enables you to optimize the speed of the MATLAB FFT functions fft,
ifft, fft2, ifft2, fftn, and ifftn. You can use fftw to set options for a tuning
algorithm that experimentally determines the fastest algorithm for computing
an FFT of a particular size and dimension at run time. MATLAB records the
optimal algorithm in an internal data base and uses it to compute FFTs of the
same size throughout the current session. The tuning algorithm is part of the
FFTW library that MATLAB uses to compute FFTs.
fftw('planner', method) sets the method by which the tuning algorithm
searches for a good FFT algorithm when the dimension of the FFT is not a
power of 2. You can specify method to be one of the following:
'estimate'
'measure'
'patient'
'exhaustive'
'hybrid'
When you call fftw('planner', method), the next time you call one of the FFT
functions, such as fft, the tuning algorithm uses the specified method to
optimize the FFT computation. Because the tuning involves trying different
algorithms, the first time you call an FFT function, it might run more slowly
than if you did not call fftw. However, subsequent calls to any of the FFT
functions, for a problem of the same size, often run more quickly than they
would without using fftw.
fftw
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