Estimate empirical transfer functions and periodograms
estimates a
transfer function of the form:g
= etfe(data
)
data
contains time- or frequency-domain input-output
data or time-series data:
If data
is time-domain input-output
signals, g
is the ratio of the output Fourier transform
to the input Fourier transform for the data.
For nonperiodic data, the transfer function is estimated at
128 equally-spaced frequencies [1:128]/128*pi/Ts
.
For periodic data that contains a whole number of periods (data.Period
= integer
), the response is computed at the frequencies k*2*pi/period
for k
= 0
up to the Nyquist frequency.
If data
is frequency-domain input-output
signals, g
is the ratio of output to input at all
frequencies, where the input is nonzero.
If data
is time-series data (no
input channels), g
is the periodogram, that is
the normed absolute square of the Fourier transform, of the data.
The corresponding spectral estimate is normalized, as described in Spectrum Normalization and
differs from the spectrum
normalization in the Signal Processing Toolbox™ product.
applies
a smoothing operation on the raw spectral estimates using a Hamming
Window that yields a frequency resolution of about g
= etfe(data
,M
)pi/M
.
The effect of M
is similar to the effect of M
in spa
. M
is ignored for
periodic data. Use this syntax as an alternative to spa
for
narrowband spectra and systems that require large values of M
.
specifies
the frequency spacing for nonperiodic data.g
= etfe(data
,M
,N
)
For nonperiodic time-domain data, N
specifies
the frequency grid [1:N]/N*pi/Ts
rad/TimeUnit.
When not specified, N
is 128.
For periodic time-domain data, N
is
ignored.
For frequency-domain data, the N
is fmin:delta_f:fmax
,
where [fmin fmax]
is the range of frequencies in data
,
and delta_f
is (fmax-fmin)/(N-1)
rad/TimeUnit.
When not specified, the response is computed at the frequencies contained
in data where input is nonzero.