fft

datf = fft(data) uses the fast Fourier transform (FFT) algorithm to transform the time-domain iddata object data to the frequency domain iddata object datf. data contains real-valued signals and has constant sample time Ts, and datf has frequency values equally distributed from 0 to the Nyquist frequency. The Nyquist frequency is included if the signal length is even and not included if the length is odd. To preserve the signal power and noise level, FFTs are normalized by dividing each transform by the square root of the signal length.

datf = fft(data,N) specifies the transformation length N. In the default case, the length of the transformation is determined by the signal length. Including N forces the FFT transformations to pad with zeros if the signals in data are shorter than N and truncate the signals otherwise. Thus, the number of frequencies in the real signal case is (N/2)+1 when N is even or (N+1)/2 when N is odd. If data contains several experiments, N can be a row vector of corresponding length.

datf = fft(data,N,'complex') specifies to include negative frequencies. For real signals, the default is that datf contains only nonnegative frequencies, while for complex-valued signals, negative frequencies are always included. To enforce negative frequencies in the real case, add 'complex'.