adaptive noise cancelling
Advanced
AIC, the Akaike Information Criterion
Akaike's Final Prediction Error (FPE)
AR model
ARARMAX structure
ARMAX
ARMAX model
ARMAX structure
ARX
ARX model <1> <2> <3> <4> <5> <6> <7>
basic tools
BJ
Bode diagram
Bode plot
Box-Jenkins (BJ) structure
Box-Jenkins model
Burg's method
communication window ident
comparisons using compare 3-51
complex-valued data
confidence interval
conventions in our documentation (table)
correlation analysis <1> <2> <3>
covariance function
covariance matrix <1> <2>
suppressing calculation
covariance method
creating models from data
cross correlation function <1> <2>
cross spectrum
customized plots
CVA
data
channels
feedback
iddata object <1> <2>
multiple experiments
representation
Data Board
data handling checklist
data representation <1> <2>
data views
delays <1> <2> <3>
detrending the data
difference equation
disturbance
disturbance spectra
drift matrix
dynamic models, introduction
empirical transfer function estimate
estimation
parametric
estimation data
estimation method
instrumental variables
nonparametric
parametric
prediction error approach <1> <2>
subspace method
estimation methods
direct
parametric
exporting to the MATLAB workspace
extended least squares (ELS)
fault detection
feedback
feedback in data
FixedParameter
focus <1> <2>
frequency
function
functions <1> <2>
plots
range
response
scales
frequency domain description
frequency response <1> <2> <3>
Gauss-Newton direction
Gauss-Newton minimization
geometric lattice method
graphical user interface (GUI)
greybox-modelling
GUI
topics
Hamming window
idarx model object
ident window
identification method
subspace
identification process, basic steps
idfrd model object
idgrey model object
idpoly model object
idss model object
importing data into the GUI
impulse response <1> <2> <3> <4>
Information Theoretic Criterion (AIC)
initial condition
initial parameter values
initial state
in GUI
state space model
innovations form <1> <2>
input signals
instrumental variable
(IV) method
technique
iterative search <1> <2>
Kalman gain <1> <2>
lag widow
lag window
layout
least squares
Levenberg-Marquard
LimitError
main ident window
maximum likelihood
criterion
method
MaxIter
MaxSize
memory horizon
merge experiments
model
nonparametric
output-error
parametric
properties
set
state-space
structure <1> <2> <3>
structure selection
uncertainty
view functions
views <1> <2>
Model Board
model order
model structure
model uncertainty
model validation
model views
MOESP
multi-output models
criterion
Multiple experiments
multivariable ARX model
multivariable systems <1> <2>
N4Horison
N4Horizon
N4Weight
na,nb,nc,nd,nf
parameter definitions
noise
noise model
noise source <1> <2>
noise-free simulation
noise-free simulations
nonequal sampling
nonparametric estimation
nonparametric identification
Normalized Gradient (NG) Approach
numerical differentiation
Nyquist plot
OE
OE model
offsets
order editor
outliers
signals
output error model
output signals
Output-Error model
output-error model <1> <2> <3>
state space model
parametric identification
parametric model
parametric model estimation
periodogram
pole
poles
poorly damped systems
prediction
error identification
error method
prediction error
prediction horizon
preferences
in GUI
prefiltering
prefiltering signals
Quickstart menu item
recursive
identification <1> <2>
parameter estimation
references list
resampling
residual analysis <1> <2>
residuals <1> <2>
robustification
sampling interval <1> <2>
SearchDirection
selecting data ranges
Sessions
shift operator <1> <2>
simulating data
spectral analysis <1> <2> <3>
spectrum <1> <2> <3> <4>
startup identification procedure
state space model
continuous time <1> <2>
innovations form
output-error model
stochastic
state variables
state vector
state-space
model
state-space model
state-space models
step response <1> <2>
structure
structure matrices
subspace method <1> <2>
time delay
time domain description
time series model <1> <2>
time-continuous systems
Tolerance
trace <1> <2>
transfer function <1> <2>
transient response <1> <2>
uncertainty
suppressing calculation
Unnormalized Gradient (UG) Approach
validation data <1> <2> <3>
white noise <1> <2>
window sizes
working data
Working Data set
Yule-Walker approach
zero
zeros