# Documentation

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# simOptions

Option set for sim

## Description

example

opt = simOptions creates the default option set for sim.

example

opt = simOptions(Name,Value) creates an option set with the options specified by one or more Name,Value pair arguments.

## Examples

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opt = simOptions;

Create an option set for sim specifying the following options.

• Zero initial conditions

• Input offset of 5 for the second input of a two-input model

opt = simOptions('InitialCondition','z','InputOffset',[0; 5]);

Create noise data for a simulation with 500 input data samples and two outputs.

noiseData = randn(500,2);

Create a default option set.

opt = simOptions;

Modify the option set to add the noise data.

opt.NoiseData = noiseData;

## Input Arguments

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### Name-Value Pair Arguments

Specify optional comma-separated pairs of Name,Value arguments. Name is the argument name and Value is the corresponding value. Name must appear inside single quotes (' '). You can specify several name and value pair arguments in any order as Name1,Value1,...,NameN,ValueN.

Example: 'AddNoise',true','InputOffset',[5;0] adds default Gaussian white noise to the response model and specifies an input offset of 5 for the first of two model inputs.

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Simulation initial conditions, specified as one of the following:

• 'z' — Zero initial conditions.

• Numerical column vector of initial states with length equal to the model order.

For multi-experiment data, specify a matrix with Ne columns, where Ne is the number of experiments, to configure the initial conditions separately for each experiment. Otherwise, use a column vector to specify the same initial conditions for all experiments.

Use this option for state-space models (idss and idgrey) only.

• Structure with the following fields, which contain the historical input and output values for a time interval immediately before the start time of the data used in the simulation:

FieldDescription
InputInput history, specified as a matrix with Nu columns, where Nu is the number of input channels. For time-series models, use [].
OutputOutput history, specified as a matrix with Ny columns, where Ny is the number of output channels.

For each field, if the respective signals are constant before the start time of the simulation, use a row vector to specify the constant values.

For multi-experiment data, you can configure the initial conditions separately for each experiment by specifying InitialCondition as a structure array with Ne elements. Otherwise, use a single structure to specify the same initial conditions for all experiments.

• 'model' — Initial conditions as specified in the InitialStates property of the model. Use this option for idnlgrey models only. This option corresponds to the default initial conditions for idnlgrey models when no simOptions option set is used.

Covariance of initial states vector, specified as one of the following:

• Positive definite matrix of size Nx-by-Nx, where Nx is the model order.

For multi-experiment data, specify as an Nx-by-Nx-by-Ne matrix, where Ne is the number of experiments.

• [] — No uncertainty in the initial states.

Use this option only for state-space models (idss and idgrey) when 'InitialCondition' is specified as a column vector. Use this option to account for initial condition uncertainty when computing the standard deviation of the simulated response of a model.

Input signal offset, specified as a column vector of length Nu. Use [] if there are no input offsets. Each element of InputOffset is subtracted from the corresponding input data before the input is used to simulate the model.

For multiexperiment data, specify InputOffset as:

• An Nu-by-Ne matrix to set offsets separately for each experiment.

• A column vector of length Nu to apply the same offset for all experiments.

Output signal offset, specified as a column vector of length Ny. Use [] if there are no output offsets. Each element of OutputOffset is added to the corresponding simulated output response of the model.

For multiexperiment data, specify OutputOffset as:

• An Ny-by-Ne matrix to set offsets separately for each experiment.

• A column vector of length Ny to apply the same offset for all experiments.

Noise addition toggle, specified as a logical value indicating whether to add noise to the response model.

Noise signal data specified as one of the following:

• [] — Default Gaussian white noise.

• Matrix with Ns rows and Ny columns, where Ns is the number of input data samples, and Ny is the number of outputs. Each matrix entry is scaled according to NoiseVariance property of the simulated model and added to the corresponding output data point. To set NoiseData at a level that is consistent with the model, use white noise with zero mean and a unit covariance matrix.

• Cell array of Ne matrices, where Ne is the number of experiments for multiexperiment data. Use a cell array to set the NoiseData separately for each experiment, otherwise set the same noise signal for all experiments using a matrix.

NoiseData is the noise signal, e(t), for the model

$y\left(t\right)=Gu\left(t\right)+He\left(t\right).$

Here,G is the transfer function from the input, u(t), to the output, y(t), and H is the noise transfer function.

NoiseData is used for simulation only when AddNoise is true.

## Output Arguments

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Option set for sim command, returned as a simOptions option set.