iddata | Time- or frequency-domain data |
idfrd | Frequency-response data or model |
idinput | Generate input signals |
sim | Simulate response of identified model |
size | Query output/input/array dimensions of input–output model and number of frequencies of FRD model |
midprefs | Specify location for file containing System Identification app startup information |
simOptions | Option set for sim |
fselect | Select frequency points or range in FRD model |
getexp | Specific experiments from multiple-experiment data set |
merge (iddata) | Merge data sets into iddata object |
fcat | Concatenate FRD models along frequency dimension |
bode | Bode plot of frequency response, or magnitude and phase data |
bodemag | Bode magnitude response of LTI models |
plot | Plot input-output data |
advice | Analysis and recommendations for data or estimated linear models |
delayest | Estimate time delay (dead time) from data |
isreal | Determine whether model parameters or data values are real |
realdata | Determine whether iddata is based on real-valued signals |
feedback | Identify possible feedback data |
pexcit | Level of excitation of input signals |
impulseest | Nonparametric impulse response estimation |
etfe | Estimate empirical transfer functions and periodograms |
spa | Estimate frequency response with fixed frequency resolution using spectral analysis |
spafdr | Estimate frequency response and spectrum using spectral analysis with frequency-dependent resolution |
iddataPlotOptions | Option set for iddata/plot |
detrend | Subtract offset or trend from time-domain signals contained in iddata objects |
retrend | Add offsets or trends to data signals |
diff | Difference signals in iddata objects |
idfilt | Filter data using user-defined passbands, general filters, or Butterworth filters |
misdata | Reconstruct missing input and output data |
nkshift | Shift data sequences |
idresamp | Resample time-domain data by decimation or interpolation |
resample | Resample time-domain data by decimation or interpolation (requires Signal Processing Toolbox software) |
getTrend | Data offset and trend information |
chgFreqUnit | Change frequency units of frequency-response data model |
fdel | Delete specified data from frequency response data (FRD) models |
TrendInfo | Offset and linear trend slope values for detrending data |
fft | Transform iddata object to frequency domain data |
ifft | Transform iddata objects from frequency to time domain |
etfe | Estimate empirical transfer functions and periodograms |
spa | Estimate frequency response with fixed frequency resolution using spectral analysis |
spafdr | Estimate frequency response and spectrum using spectral analysis with frequency-dependent resolution |
procest | Estimate process model using time or frequency data |
idproc | Continuous-time process model with identifiable parameters |
pem | Prediction error estimate for linear and nonlinear model |
idpar | Create parameter for initial states and input level estimation |
delayest | Estimate time delay (dead time) from data |
init | Set or randomize initial parameter values |
getpvec | Model parameters and associated uncertainty data |
setpvec | Modify value of model parameters |
getpar | Obtain attributes such as values and bounds of linear model parameters |
setpar | Set attributes such as values and bounds of linear model parameters |
procestOptions | Options set for procest |
arx | Estimate parameters of ARX or AR model using least squares |
armax | Estimate parameters of ARMAX model using time-domain data |
bj | Estimate Box-Jenkins polynomial model using time domain data |
iv4 | ARX model estimation using four-stage instrumental variable method |
ivx | ARX model estimation using instrumental variable method with arbitrary instruments |
oe | Estimate Output-Error polynomial model using time or frequency domain data |
polyest | Estimate polynomial model using time- or frequency-domain data |
idpoly | Polynomial model with identifiable parameters |
pem | Prediction error estimate for linear and nonlinear model |
arxstruc | Compute loss functions for single-output ARX models |
ivstruc | Compute loss functions for sets of ARX model structures using instrumental variable method |
selstruc | Select model order for single-output ARX models |
struc | Generate model-order combinations for single-output ARX model estimation |
arxRegul | Determine regularization constants for ARX model estimation |
delayest | Estimate time delay (dead time) from data |
init | Set or randomize initial parameter values |
polydata | Access polynomial coefficients and uncertainties of identified model |
getpvec | Model parameters and associated uncertainty data |
setpvec | Modify value of model parameters |
getpar | Obtain attributes such as values and bounds of linear model parameters |
setpar | Set attributes such as values and bounds of linear model parameters |
setPolyFormat | Specify format for B and F polynomials of multi-input polynomial model |
armaxOptions | Option set for armax |
arxOptions | Option set for arx |
arxRegulOptions | Option set for arxRegul |
bjOptions | Option set for bj |
iv4Options | Option set for iv4 |
oeOptions | Option set for oe |
polyestOptions | Option set for polyest |
ssest | Estimate state-space model using time or frequency domain data |
ssregest | Estimate state-space model by reduction of regularized ARX model |
n4sid | Estimate state-space model using subspace method |
idss | State-space model with identifiable parameters |
pem | Prediction error estimate for linear and nonlinear model |
delayest | Estimate time delay (dead time) from data |
getpvec | Model parameters and associated uncertainty data |
setpvec | Modify value of model parameters |
getpar | Obtain attributes such as values and bounds of linear model parameters |
setpar | Set attributes such as values and bounds of linear model parameters |
ssform | Quick configuration of state-space model structure |
init | Set or randomize initial parameter values |
idpar | Create parameter for initial states and input level estimation |
idssdata | State-space data of identified system |
findstates | Estimate initial states of model |
ssestOptions | Option set for ssest |
ssregestOptions | Option set for ssregest |
n4sidOptions | Option set for n4sid |
findstatesOptions | Option set for findstates |
tfest | Transfer function estimation |
idtf | Transfer function model with identifiable parameters |
pem | Prediction error estimate for linear and nonlinear model |
delayest | Estimate time delay (dead time) from data |
getpvec | Model parameters and associated uncertainty data |
setpvec | Modify value of model parameters |
getpar | Obtain attributes such as values and bounds of linear model parameters |
setpar | Set attributes such as values and bounds of linear model parameters |
tfdata | Access transfer function data |
init | Set or randomize initial parameter values |
tfestOptions | Option set for tfest |
greyest | Linear grey-box model estimation |
idgrey | Linear ODE (grey-box model) with identifiable parameters |
pem | Prediction error estimate for linear and nonlinear model |
findstates | Estimate initial states of model |
init | Set or randomize initial parameter values |
getpvec | Model parameters and associated uncertainty data |
setpvec | Modify value of model parameters |
getpar | Obtain attributes such as values and bounds of linear model parameters |
setpar | Set attributes such as values and bounds of linear model parameters |
findstatesOptions | Option set for findstates |
greyestOptions | Option set for greyest |
etfe | Estimate empirical transfer functions and periodograms |
spa | Estimate frequency response with fixed frequency resolution using spectral analysis |
spafdr | Estimate frequency response and spectrum using spectral analysis with frequency-dependent resolution |
idfrd | Frequency-response data or model |
getpvec | Model parameters and associated uncertainty data |
setpvec | Modify value of model parameters |
bode | Bode plot of frequency response, or magnitude and phase data |
bodemag | Bode magnitude response of LTI models |
freqresp | Frequency response over grid |
chgFreqUnit | Change frequency units of frequency-response data model |
cra | Estimate impulse response using prewhitened-based correlation analysis |
impulseest | Nonparametric impulse response estimation |
getpvec | Model parameters and associated uncertainty data |
setpvec | Modify value of model parameters |
impulseestOptions | Options set for impulseest |
idnlarx | Nonlinear ARX model |
nlarx | Estimate parameters of nonlinear ARX model |
nlarxOptions | Option set for nlarx |
isnlarx | Detect nonlinearity in estimation data |
init | Set or randomize initial parameter values |
getpvec | Model parameters and associated uncertainty data |
setpvec | Modify value of model parameters |
polyreg | Powers and products of standard regressors |
customreg | Custom regressor for nonlinear ARX models |
addreg | Add custom regressors to nonlinear ARX model |
getreg | Regressor expressions and numerical values in nonlinear ARX model |
customnet | Custom nonlinearity estimator for nonlinear ARX and Hammerstein-Wiener models |
linear | Class representing linear nonlinearity estimator for nonlinear ARX models |
neuralnet | Class representing neural network nonlinearity estimator for nonlinear ARX models |
treepartition | Class representing binary-tree nonlinearity estimator for nonlinear ARX models |
wavenet | Create a wavelet network nonlinearity estimator object |
sigmoidnet | Class representing sigmoid network nonlinearity estimator for nonlinear ARX and Hammerstein-Wiener models |
evaluate | Value of nonlinearity estimator at given input |
sim | Simulate response of identified model |
simOptions | Option set for sim |
predict | Predict K-step ahead model output |
predictOptions | Option set for predict |
compare | Compare identified model output and measured output |
compareOptions | Option set for compare |
forecast | Forecast identified model output |
forecastOptions | Option set for forecast |
plot | Plot nonlinearity of nonlinear ARX model |
evaluate | Value of nonlinearity estimator at given input |
getDelayInfo | Get input/output delay information for idnlarx model structure |
findop | Compute operating point for Nonlinear ARX model |
findopOptions | Option set for findop |
operspec | Construct operating point specification object for idnlarx model |
linearize | Linearize nonlinear ARX model |
linapp | Linear approximation of nonlinear ARX and Hammerstein-Wiener models for given input |
idnlhw | Hammerstein-Wiener model |
nlhw | Estimate Hammerstein-Wiener model |
nlhwOptions | Option set for nlhw |
init | Set or randomize initial parameter values |
getpvec | Model parameters and associated uncertainty data |
setpvec | Modify value of model parameters |
customnet | Custom nonlinearity estimator for nonlinear ARX and Hammerstein-Wiener models |
deadzone | Create a dead-zone nonlinearity estimator object |
poly1d | Class representing single-variable polynomial nonlinear estimator for Hammerstein-Wiener models |
pwlinear | Create a piecewise-linear nonlinearity estimator object |
saturation | Create a saturation nonlinearity estimator object |
sigmoidnet | Class representing sigmoid network nonlinearity estimator for nonlinear ARX and Hammerstein-Wiener models |
unitgain | Specify absence of nonlinearities for specific input or output channels in Hammerstein-Wiener models |
wavenet | Create a wavelet network nonlinearity estimator object |
evaluate | Value of nonlinearity estimator at given input |
sim | Simulate response of identified model |
simOptions | Option set for sim |
compare | Compare identified model output and measured output |
compareOptions | Option set for compare |
plot | Plot input and output nonlinearity, and linear responses of Hammerstein-Wiener model |
evaluate | Value of nonlinearity estimator at given input |
findop | Compute operating point for Hammerstein-Wiener model |
findopOptions | Option set for findop |
operspec | Construct operating point specification object for idnlhw model |
linearize | Linearize Hammerstein-Wiener model |
linapp | Linear approximation of nonlinear ARX and Hammerstein-Wiener models for given input |
nlgreyest | Estimate nonlinear grey-box model parameters |
idnlgrey | Nonlinear grey-box model |
pem | Prediction error estimate for linear and nonlinear model |
findstates | Estimate initial states of model |
init | Set or randomize initial parameter values |
getinit | Values of idnlgrey model initial states |
setinit | Set initial states of idnlgrey model object |
getpar | Parameter values and properties of idnlgrey model parameters |
setpar | Set initial parameter values of idnlgrey model object |
getpvec | Model parameters and associated uncertainty data |
setpvec | Modify value of model parameters |
sim | Simulate response of identified model |
nlgreyestOptions | Option set for nlgreyest |
findstatesOptions | Option set for findstates |
simOptions | Option set for sim |
greyest | Linear grey-box model estimation |
nlgreyest | Estimate nonlinear grey-box model parameters |
idgrey | Linear ODE (grey-box model) with identifiable parameters |
idnlgrey | Nonlinear grey-box model |
pem | Prediction error estimate for linear and nonlinear model |
findstates | Estimate initial states of model |
init | Set or randomize initial parameter values |
getinit | Values of idnlgrey model initial states |
setinit | Set initial states of idnlgrey model object |
getpar | Parameter values and properties of idnlgrey model parameters |
setpar | Set initial parameter values of idnlgrey model object |
getpvec | Model parameters and associated uncertainty data |
setpvec | Modify value of model parameters |
sim | Simulate response of identified model |
greyestOptions | Option set for greyest |
nlgreyestOptions | Option set for nlgreyest |
findstatesOptions | Option set for findstates |
simOptions | Option set for sim |
compare | Compare identified model output and measured output |
compareOptions | Option set for compare |
goodnessOfFit | Goodness of fit between test and reference data |
predict | Predict state and state estimation error covariance at next time step using extended or unscented Kalman filter, or particle filter |
predictOptions | Option set for predict |
sim | Simulate response of identified model |
simOptions | Option set for sim |
findstates | Estimate initial states of model |
findstatesOptions | Option set for findstates |
data2state | Map past data to states of state-space and nonlinear ARX models |
idpar | Create parameter for initial states and input level estimation |
present | Display model information, including estimated uncertainty |
simsd | Simulate linear models with uncertainty using Monte Carlo method |
freqresp | Frequency response over grid |
rsample | Random sampling of linear identified systems |
showConfidence | Display confidence regions on response plots for identified models |
getcov | Parameter covariance of identified model |
setcov | Set parameter covariance data in identified model |
translatecov | Translate parameter covariance across model transformation operations |
step | Step response plot of dynamic system; step response data |
stepplot | Plot step response and return plot handle |
impulse | Impulse response plot of dynamic system; impulse response data |
bode | Bode plot of frequency response, or magnitude and phase data |
bodemag | Bode magnitude response of LTI models |
nyquist | Nyquist plot of frequency response |
nyquistplot | Nyquist plot with additional plot customization options |
iopzmap | Plot pole-zero map for I/O pairs of model |
iopzplot | Plot pole-zero map for I/O pairs and return plot handle |
tfdata | Access transfer function data |
zpkdata | Access zero-pole-gain data |
simsdOptions | Option set for simsd |
c2d | Convert model from continuous to discrete time |
d2c | Convert model from discrete to continuous time |
d2d | Resample discrete-time model |
translatecov | Translate parameter covariance across model transformation operations |
c2dOptions | Create option set for continuous- to discrete-time conversions |
d2cOptions | Create option set for discrete- to continuous-time conversions |
d2dOptions | Create option set for discrete-time resampling |
idfrd | Frequency-response data or model |
idpoly | Polynomial model with identifiable parameters |
idtf | Transfer function model with identifiable parameters |
idss | State-space model with identifiable parameters |
canon | State-space canonical realization |
balred | Model order reduction |
noisecnv | Transform identified linear model with noise channels to model with measured channels only |
translatecov | Translate parameter covariance across model transformation operations |
merge | Merge estimated models |
append | Group models by appending their inputs and outputs |
noise2meas | Noise component of model |
absorbDelay | Replace time delays by poles at z = 0 or phase shift |
chgTimeUnit | Change time units of dynamic system |
chgFreqUnit | Change frequency units of frequency-response data model |
fdel | Delete specified data from frequency response data (FRD) models |
stack | Build model array by stacking models or model arrays along array dimensions |
ss2ss | State coordinate transformation for state-space model |
linapp | Linear approximation of nonlinear ARX and Hammerstein-Wiener models for given input |
idnlarx/findop | Compute operating point for Nonlinear ARX model |
idnlarx/linearize | Linearize nonlinear ARX model |
idnlhw/findop | Compute operating point for Hammerstein-Wiener model |
idnlhw/linearize | Linearize Hammerstein-Wiener model |
findopOptions | Option set for findop |
polydata | Access polynomial coefficients and uncertainties of identified model |
ssdata | Access state-space model data |
idssdata | State-space data of identified system |
tfdata | Access transfer function data |
zpkdata | Access zero-pole-gain data |
frdata | Access data for frequency response data (FRD) object |
freqresp | Frequency response over grid |
getpvec | Model parameters and associated uncertainty data |
setpvec | Modify value of model parameters |
getcov | Parameter covariance of identified model |
setcov | Set parameter covariance data in identified model |
get | Access model property values |
set | Set or modify model properties |
nparams | Number of model parameters |
ndims | Query number of dimensions of dynamic system model or model array |
order | Query model order |
pole | Poles of dynamic system |
zero | Zeros and gain of SISO dynamic system |
size | Query output/input/array dimensions of input–output model and number of frequencies of FRD model |
damp | Natural frequency and damping ratio |
dcgain | Low-frequency (DC) gain of LTI system |
bandwidth | Frequency response bandwidth |
sim | Simulate response of identified model |
simOptions | Option set for sim |
simsd | Simulate linear models with uncertainty using Monte Carlo method |
simsdOptions | Option set for simsd |
predict | Predict K-step ahead model output |
predictOptions | Option set for predict |
forecast | Forecast identified model output |
forecastOptions | Option set for forecast |
idinput | Generate input signals |
sim | Simulate response of identified model |
bode | Bode plot of frequency response, or magnitude and phase data |
bodeplot | Plot Bode frequency response with additional plot customization options |
bodemag | Bode magnitude response of LTI models |
step | Step response plot of dynamic system; step response data |
stepplot | Plot step response and return plot handle |
stepinfo | Rise time, settling time, and other step-response characteristics |
nyquist | Nyquist plot of frequency response |
nyquistplot | Nyquist plot with additional plot customization options |
impulse | Impulse response plot of dynamic system; impulse response data |
impulseplot | Plot impulse response and return plot handle |
pzmap | Pole-zero plot of dynamic system |
pzplot | Pole-zero plot of dynamic system model with plot customization options |
iopzmap | Plot pole-zero map for I/O pairs of model |
iopzplot | Plot pole-zero map for I/O pairs and return plot handle |
spectrum | Output power spectrum of time series models |
spectrumplot | Plot disturbance spectrum of linear identified models |
lsim | Simulate time response of dynamic system to arbitrary inputs |
lsimplot | Simulate response of dynamic system to arbitrary inputs and return plot handle |
lsiminfo | Compute linear response characteristics |
showConfidence | Display confidence regions on response plots for identified models |
findstates | Estimate initial states of model |
data2state | Map past data to states of state-space and nonlinear ARX models |
simOptions | Option set for sim |
stepDataOptions | Options set for step |
bodeoptions | Create list of Bode plot options |
nyquistoptions | List of Nyquist plot options |
timeoptions | Create list of time plot options |
getoptions | Return @PlotOptions handle or plot options property |
setoptions | Set plot options for response plot |
pzoptions | Create list of pole/zero plot options |
spectrumoptions | Option set for spectrumplot |
identpref | Set System Identification Toolbox preferences |
findstatesOptions | Option set for findstates |
ar | Estimate parameters of AR model for scalar time series |
armax | Estimate parameters of ARMAX model using time-domain data |
arx | Estimate parameters of ARX or AR model using least squares |
etfe | Estimate empirical transfer functions and periodograms |
spa | Estimate frequency response with fixed frequency resolution using spectral analysis |
spafdr | Estimate frequency response and spectrum using spectral analysis with frequency-dependent resolution |
ivar | AR model estimation using instrumental variable method |
n4sid | Estimate state-space model using subspace method |
ssest | Estimate state-space model using time or frequency domain data |
pem | Prediction error estimate for linear and nonlinear model |
nlarx | Estimate parameters of nonlinear ARX model |
idpoly | Polynomial model with identifiable parameters |
idss | State-space model with identifiable parameters |
idnlarx | Nonlinear ARX model |
getpvec | Model parameters and associated uncertainty data |
setpvec | Modify value of model parameters |
init | Set or randomize initial parameter values |
noise2meas | Noise component of model |
spectrum | Output power spectrum of time series models |
forecast | Forecast identified model output |
sim | Simulate response of identified model |
arOptions | Option set for ar |
forecastOptions | Option set for forecast |
simOptions | Option set for sim |
recursiveAR | Create System object for online parameter estimation of AR model |
recursiveARMA | Create System object for online parameter estimation of ARMA model |
recursiveARX | Create System object for online parameter estimation of ARX model |
recursiveARMAX | Create System object for online parameter estimation of ARMAX model |
recursiveBJ | Create System object for online parameter estimation of Box-Jenkins polynomial model |
recursiveOE | Create System object for online parameter estimation of Output-Error polynomial model |
recursiveLS | Create System object for online parameter estimation using recursive least squares algorithm |
step | Update model parameters and output online using recursive estimation algorithm |
clone | Copy online parameter estimation System object |
reset | Reset online parameter estimation System object |
release | Unlock online parameter estimation System object |
isLocked | Locked status of online parameter estimation System object |
rpem | Estimate general input-output models using recursive prediction-error minimization method |
rplr | Estimate general input-output models using recursive pseudolinear regression method |
segment | Segment data and estimate models for each segment |
extendedKalmanFilter | Create extended Kalman filter object for online state estimation |
unscentedKalmanFilter | Create unscented Kalman filter object for online state estimation |
particleFilter | Particle filter object for online state estimation |
correct | Correct state and state estimation error covariance using extended or unscented Kalman filter, or particle filter and measurements |
predict | Predict state and state estimation error covariance at next time step using extended or unscented Kalman filter, or particle filter |
initialize | Initialize the state of the particle filter |
clone | Copy online state estimation object |