| Preparing Data | Construct data objects and input signals, filter,
resample, detrend, transform, identify delay and feedback, and get
and set data properties | | Identifying Linear Models | Estimate nonparametric models using correlation and
spectral analysis, compute impulse and step response, and estimate
empirical transfer functions, estimate discrete- and continuous-time
linear polynomial transfer functions and state-space models from time-
and frequency-domain data, and select model structure and order based
on loss function, AIC, and MDL criteria | | Identifying Nonlinear Black-Box Models | Estimate input-output, black-box nonlinear models,
including nonlinear ARX and Hammerstein-Wiener models | | Estimating ODE Parameters | Estimate linear and nonlinear grey-box models, set
initial parameters and initial state values, and randomize initial
parameter values | | Recursive Techniques for Identifying Linear Models | Recursively estimate input-output linear models, such
as AR, ARX, ARMAX, Box-Jenkins, and Output-Error models | | Validating and Analyzing Models | Validate and analyze models by comparing model output,
plotting models with confidence regions, computing standard deviation
and prediction errors, computing loss function, getting advice on
estimated models, and extracting numerical information from linear
models | | Simulating and Predicting Model Output | Simulate and predict model output, compute prediction
errors, and generate input data | | Using Models with Other Products | Reduce model order, convert between System Identification Toolbox™ and
LTI objects, and perform linear analysis using LTI Viewer | | Customizing and Using GUI | Start System Identification Toolbox™ GUI
and set preferences |
|
| advice | Analysis and recommendations for data or estimated linear
polynomial and state-space models |
| covf | Estimate covariance functions for time-domain iddata object |
| delayest | Estimate time delay (dead time) from data |
| detrend | Subtract trend from time-domain, frequency-domain, or
time-series data signal |
| diff | Difference signals in iddata objects |
| fcat | Concatenate frequency-domain signals in idfrd and iddata objects |
| feedback | Identify possible feedback in iddata data |
| fft | Transform iddata object to frequency
domain |
| fselect | Frequencies from idfrd object |
| get | Query properties of data and model objects |
| getexp | Specific experiment(s) from multiple-experiment iddata object |
| iddata | Class for storing time-domain and frequency-domain data |
| idfilt | Filter data using user-defined passbands, general filters,
or Butterworth filters |
| idfrd | Class for storing frequency-response or spectral-analysis
data or frequency-response models |
| idinput | Generate input signals |
| idresamp | Resample time-domain data by decimation or interpolation |
| ifft | Transform iddata objects from frequency
to time domain |
| isreal | Determine whether model parameters or data values are
real |
| merge (iddata) | Merge data sets into one iddata object |
| misdata | Reconstruct missing input and output data |
| nkshift | Shift data sequences |
| pexcit | Level of excitation of input signals |
| plot | Plot iddata or model objects |
| realdata | Determine whether iddata is based on
real-valued signals |
| resample | Resample time-domain data by decimation or interpolation
(requires Signal Processing Toolbox™ software) |
| set | Set properties of data and model objects |
| size | Dimensions of iddata, idmodel, and idfrd objects |
| timestamp | Return date and time when object was created or last modified |
| ar | Estimate parameters of AR model for scalar time series
returning idpoly object |
| armax | Estimate parameters of ARMAX or ARMA model returning idpoly object |
| arx | Estimate parameters of ARX or AR model using least squares
returning idpoly or idarx object |
| arxdata | ARX parameters from multiple-output idarx or single-output idpoly objects with variance
information |
| arxstruc | Compute and compare loss functions for single-output ARX
models |
| balred | Reduce model order (requires Control System
Toolbox™ product) |
| bj | Estimate parameters of Box-Jenkins model returning idpoly object |
| c2d | Convert model from continuous to discrete time |
| cra | Estimate impulse response using prewhitened-based correlation
analysis |
| d2c | Convert model from discrete to continuous time |
| delayest | Estimate time delay (dead time) from data |
| etfe | Estimate empirical transfer functions and periodograms
returning idfrd object |
| feedback | Identify possible feedback in iddata data |
| freqresp | Frequency-response data from idmodel or idfrd object |
| get | Query properties of data and model objects |
| idarx | Class for storing multiple-output ARX polynomials and
estimated impulse- and step-response models |
| idfrd | Class for storing frequency-response or spectral-analysis
data or frequency-response models |
| idgrey | Class for storing linear ODE models |
| idmodel | Superclass for linear models |
| idpoly | Class for storing linear polynomial input-output models |
| idproc | Class for storing low-order, continuous-time process models |
| idss | Class for storing linear state-space models with known
and unknown parameters |
| impulse | Plot impulse response with confidence interval |
| init | Set or randomize initial parameter values |
| iv4 | Estimate ARX model using four-stage instrumental variable
method returning idpoly or idarx object |
| ivar | Estimate AR model using instrumental variable method returning idpoly object |
| ivstruc | Compute loss functions for sets of output-error model
structures |
| ivx | Estimate parameters of ARX model using instrumental variable
method with arbitrary instruments returning idpoly or idarx object |
| merge | Merge estimated idmodel models |
| n4sid | Estimate state-space models using subspace method returning idss object |
| nuderst | Set step size for numerical differentiation |
| oe | Estimate parameters of output-error model returning idpoly object |
| pem | Estimate model parameters using iterative prediction-error
minimization method |
| pexcit | Level of excitation of input signals |
| polydata | Polynomial model parameters from single-input and single-output idpoly object |
| selstruc | Select model order for single-output ARX models |
| set | Set properties of data and model objects |
| setpname | Set mnemonic parameter names for black-box model structures |
| setstruc | Set matrix structure for idss objects |
| size | Dimensions of iddata, idmodel, and idfrd objects |
| spa | Estimate frequency response and spectrum using spectral
analysis returning idfrd object |
| spafdr | Estimate frequency response and spectrum using spectral
analysis with frequency-dependent resolution returning idfrd object |
| ssdata | State-space matrices from idmodel object |
| step | Plot step response with confidence interval |
| struc | Generate model structure matrices for single-input and
single-output systems |
| tfdata | Numerator and denominator of transfer function from idmodel object |
| timestamp | Return date and time when object was created or last modified |
| zpkdata | Zeros, poles, and gains of transfer function from idmodel object |
| addreg | Add custom regressors to idnalrx model |
| customnet | Class representing nonlinearity estimator with user-defined
unit function for nonlinear ARX and Hammerstein-Wiener models |
| customreg | Class representing custom regressor for nonlinear ARX
models |
| data2state(idnlarx) | Map past input/output data to current states of idnlarx model |
| deadzone | Class representing dead-zone nonlinearity estimator for
Hammerstein-Wiener models |
| evaluate | Value of nonlinearity estimator at given input |
| findop(idnlarx) | Compute operating point for nonlinear ARX model |
| findop(idnlhw) | Compute operating point for Hammerstein-Wiener model |
| get | Query properties of data and model objects |
| getDelayInfo(idnlarx) | Get input/output delay information for idnlarx model structure |
| getreg | Names of standard or custom regressors in nonlinear ARX
model |
| idnlarx | Class representing nonlinear ARX models |
| idnlhw | Class representing Hammerstein-Wiener input-output models |
| idnlmodel | Superclass for nonlinear models |
| init | Set or randomize initial parameter values |
| linapp | Linear approximation of nonlinear ARX and Hammerstein-Wiener
models for given input |
| linear | Specify to estimate nonlinear ARX model that is linear
in (nonlinear) custom regressors |
| linearize(idnlarx) | Linearize nonlinear ARX model |
| linearize(idnlhw) | Linearize Hammerstein-Wiener model |
| neuralnet | Class representing neural network object created in Neural Network Toolbox™ product for estimating nonlinear
ARX and Hammerstein-Wiener models |
| nlarx | Estimate nonlinear ARX models |
| nlhw | Estimate Hammerstein-Wiener models |
| operspec(idnlarx) | Construct operating point specification object for idnlarx model |
| operspec(idnlhw) | Construct operating point specification object for idnlhw model |
| pem | Estimate model parameters using iterative prediction-error
minimization method |
| poly1d | Class representing single-variable polynomial nonlinear
estimator for Hammerstein-Wiener models |
| polyreg | Generate custom regressors by computing powers and products
of standard regressors |
| pwlinear | Class representing piecewise-linear nonlinear estimator
for Hammerstein-Wiener models |
| saturation | Class representing saturation nonlinearity estimator for
Hammerstein-Wiener models |
| set | Set properties of data and model objects |
| sigmoidnet | Class representing sigmoid network nonlinearity estimator
for nonlinear ARX and Hammerstein-Wiener models |
| treepartition | Class representing binary-tree nonlinearity estimator
for nonlinear ARX models |
| unitgain | Specify absence of nonlinearities for specific input or
output channels in Hammerstein-Wiener models |
| wavenet | Class representing wavelet network nonlinearity estimator
for nonlinear ARX and Hammerstein-Wiener models |
| advice | Analysis and recommendations for data or estimated linear
polynomial and state-space models |
| aic | Akaike Information Criterion for estimated model |
| arxdata | ARX parameters from multiple-output idarx or single-output idpoly objects with variance
information |
| bode | Plot Bode diagram of frequency response with confidence
interval |
| compare | Compare model output and measured output |
| ffplot | Plot frequency response and spectra |
| fpe | Akaike Final Prediction Error for estimated model |
| freqresp | Frequency-response data from idmodel or idfrd object |
| fselect | Frequencies from idfrd object |
| impulse | Plot impulse response with confidence interval |
| isreal | Determine whether model parameters or data values are
real |
| ivstruc | Compute loss functions for sets of output-error model
structures |
| noisecnv | Transform idmodel object with noise
channels to model with measured channels only |
| nyquist | Plot Nyquist curve of frequency response with confidence
interval |
| pe | Prediction errors associated with model and data set |
| plot | Plot iddata or model objects |
| polydata | Polynomial model parameters from single-input and single-output idpoly object |
| predict | Predict output k steps ahead |
| predict(idnlarx) | Predict output k steps ahead for nonlinear
ARX model |
| predict(idnlgrey) | Predict output k steps ahead for nonlinear
ODE model |
| predict(idnlhw) | Predict output k steps ahead for Hammerstein-Wiener
model |
| present | Display model information, including estimated uncertainty |
| pzmap | Plot zeros and poles with confidence interval |
| resid | Compute and test model residuals (prediction errors) |
| selstruc | Select model order for single-output ARX models |
| sim | Simulate linear models with confidence interval |
| sim(idnlarx) | Simulate nonlinear ARX model |
| sim(idnlgrey) | Simulate nonlinear ODE model |
| sim(idnlhw) | Simulate Hammerstein-Wiener model |
| simsd | Simulate models with uncertainty using Monte Carlo method |
| ssdata | State-space matrices from idmodel object |
| step | Plot step response with confidence interval |
| tfdata | Numerator and denominator of transfer function from idmodel object |
| view | Plot model characteristics using Control System Toolbox™ LTI
Viewer GUI |
| zpkdata | Zeros, poles, and gains of transfer function from idmodel object |
Alphabetical List