| 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 offset or trend from data signals |
| diff | Difference signals in iddata objects |
| fcat | Concatenate frequency-domain signals in data objects |
| feedback | Identify possible feedback data |
| fft | Transform iddata object to frequency
domain data |
| fselect | Frequencies from frequency response data |
| get | Query properties of data and model objects |
| getexp | Specific experiments from multiple-experiment data set |
| getTrend | Data offset and trend information |
| iddata | Time- or frequency-domain data |
| idfilt | Filter data using user-defined passbands, general filters,
or Butterworth filters |
| idfrd | Frequency-response data or model |
| 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 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 data and model objects |
| timestamp | Return date and time when object was created or last modified |
| TrendInfo | Offset and linear trend slope values for detrending data |
| ar | Estimate parameters of AR model for scalar time series |
| armax | Estimate parameters of ARMAX or ARMA model |
| arx | Estimate parameters of ARX or AR model using least squares |
| arxdata | ARX parameters from multiple-output models with variance
information |
| arxstruc | Compute and compare loss functions for single-output ARX
models |
| balred | Reduce model order (requires Control System Toolbox product) |
| bj | Box-Jenkins (BJ) model estimation |
| c2d | Transform linear model from continuous to discrete time |
| cra | Estimate impulse response using prewhitened-based correlation
analysis |
| d2c | Transform linear model from discrete to continuous time |
| delayest | Estimate time delay (dead time) from data |
| etfe | Estimate empirical transfer functions and periodograms |
| feedback | Identify possible feedback data |
| frd | Convert idfrd objects to Control System Toolbox frequency-response
LTI model |
| freqresp | Frequency response data from linear models |
| get | Query properties of data and model objects |
| idarx | Multiple-output ARX polynomials, impulse response, or
step response model |
| idfrd | Frequency-response data or model |
| idgrey | Linear ODE (grey-box model) with known and unknown parameters |
| idmodel | Superclass for linear models |
| idpoly | Linear polynomial input-output model |
| idproc | Linear, low-order, continuous-time transfer function |
| idss | State-space model |
| impulse | Plot impulse response with confidence interval |
| init | Set or randomize initial parameter values |
| iv4 | Estimate ARX model using four-stage instrumental variable
method |
| ivar | Estimate AR model using instrumental variable method |
| ivstruc | Loss functions for sets of ARX model structures |
| ivx | Estimate parameters of ARX model using instrumental variable
method with arbitrary instruments |
| LTI Commands | Apply Control System Toolbox commands to linear model |
| merge | Merge estimated models |
| n4sid | Estimate state-space models using subspace method |
| nuderst | Set step size for numerical differentiation |
| oe | Output-error (OE) model parameter estimation |
| pem | Estimate model parameters using iterative prediction-error
minimization method |
| pexcit | Level of excitation of input signals |
| polydata | Parameters from single-input and single-output polynomial
model |
| selstruc | Select model order for single-output ARX models |
| set | Set properties of data and model objects |
| setpname | Set mnemonic parameter names for linear black-box model
structures |
| setPolyFormat | Specify format for B and F polynomials of multi-input
polynomial model for backward compatibility |
| setstruc | Set matrix structure for idss model objects |
| size | Dimensions of data and model objects |
| spa | Estimate frequency response with fixed frequency resolution
using spectral analysis |
| spafdr | Estimate frequency response and spectrum using spectral
analysis with frequency-dependent resolution |
| ss | Convert linear models to Control System Toolbox LTI
models |
| ssdata | State-space matrices from parametric linear model |
| step | Plot step response with confidence interval |
| struc | Generate model-order combinations for single-output ARX
model estimation |
| tf | Convert linear models to transfer-function Control System Toolbox LTI
models |
| tfdata | Numerator and denominator of transfer function from linear
model |
| timestamp | Return date and time when object was created or last modified |
| zpk | Convert linear model to Control System Toolbox state-space
LTI models |
| zpkdata | Zeros, poles, and gains of transfer function from linear
model |
| addreg | Add custom regressors to nonlinear ARX model |
| customnet | Custom nonlinearity estimator for nonlinear ARX and Hammerstein-Wiener
models |
| customreg | Custom regressor for nonlinear ARX models |
| data2state(idnlarx) | Map past input/output data to current states of nonlinear
ARX 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 | Get input/output delay information for idnlarx model
structure |
| getreg | Regressor expressions and numerical values in nonlinear
ARX model |
| idnlarx | Nonlinear ARX model |
| idnlhw | Hammerstein-Wiener model |
| 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 | Class representing linear nonlinearity estimator for nonlinear
ARX models |
| linearize(idnlarx) | Linearize nonlinear ARX model |
| linearize(idnlhw) | Linearize Hammerstein-Wiener model |
| neuralnet | Class representing neural network nonlinearity estimator
for nonlinear ARX models |
| nlarx | Estimate nonlinear ARX model |
| nlhw | Estimate Hammerstein-Wiener model |
| 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 | 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 models with variance
information |
| balred | Reduce model order (requires Control System Toolbox product) |
| bode | Compute and plot frequency response magnitude and phase
for logarithmic frequencies |
| compare | Compare model output and measured output |
| ffplot | Compute and plot frequency response magnitude and phase
for linear frequencies |
| fpe | Akaike Final Prediction Error for estimated model |
| freqresp | Frequency response data from linear models |
| fselect | Frequencies from frequency response data |
| impulse | Plot impulse response with confidence interval |
| isreal | Determine whether model parameters or data values are
real |
| ivstruc | Loss functions for sets of ARX 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 | Parameters from single-input and single-output polynomial
model |
| 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 parametric linear model |
| step | Plot step response with confidence interval |
| tfdata | Numerator and denominator of transfer function from linear
model |
| view | Plot model characteristics using Control System Toolbox LTI
Viewer GUI |
| zpkdata | Zeros, poles, and gains of transfer function from linear
model |
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