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arxRegulOptions

Option set for arxRegul

Syntax

  • opt = arxRegulOptions
    example
  • opt = arxRegulOptions(Name,Value)
    example

Description

example

opt = arxRegulOptions creates a default option set for arxRegul.

example

opt = arxRegulOptions(Name,Value) creates an options set with the options specified by one or more name-value pair arguments.

Examples

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opt = arxRegulOptions;
opt = arxRegulOptions('RegulKernel','DC');

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: option = arxRegulOptions('RegulKernel', 'DC') specifies 'DC' as the regularization kernel.

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Regularization kernel, specified as one of the following values:

  • 'TC' — Tuned and correlated kernel

  • 'SE' — Squared exponential kernel

  • 'SS' — Stable spline kernel

  • 'HF' — High frequency stable spline kernel

  • 'DI' — Diagonal kernel

  • 'DC' — Diagonal and correlated kernel

The specified kernel is used for regularized estimation of impulse response for all input-output channels. Regularization reduces variance of estimated model coefficients and produces a smoother response by trading variance for bias.

For more information about these choices, see [1].

Data Types: char

Offset levels present in the input signals of time-domain estimation data, specified as one of the following:

  • An Nu-element column vector, where Nu is the number of inputs. For multi-experiment data, specify a Nu-by-Ne matrix, where Ne is the number of experiments. The offset value InputOffset(i,j) is subtracted from the ith input signal of the jth experiment.

  • [] — No offsets.

Data Types: double

Output signal offset level of time-domain estimation data, specified as one of the following:

  • An Ny-element column vector, where Ny is the number of outputs. For multi-experiment data, specify a Ny-by-Ne matrix, where Ne is the number of experiments. The offset value OputOffset(i,j) is subtracted from the ith output signal of the jth experiment.

  • [] — No offsets.

The specified values are subtracted from the output signals before using them for estimation.

Data Types: double

Advanced options for regularized estimation, specified as a structure with the following fields:

  • MaxSize — Maximum allowable size of Jacobian matrices formed during estimation, specified as a large positive number.

    Default: 250e3

  • SearchMethod — Search method for estimating regularization parameters, specified as one of the following values:

    • 'gn': Quasi-Newton line search.

    • 'fmincon': Trust-region-reflective constrained minimizer. In general, 'fmincon' is better than 'gn' for handling bounds on regularization parameters that are imposed automatically during estimation. Requires Optimization Toolbox™ software.

    Default: 'gn'

    If you have the Optimization Toolbox software, the default is 'fmincon'.

Output Arguments

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Regularization options, returned as an arxRegulOptions options set.

References

[1] T. Chen, H. Ohlsson, and L. Ljung. "On the Estimation of Transfer Functions, Regularizations and Gaussian Processes - Revisited", Automatica, Volume 48, August 2012.

See Also

Introduced in R2014a

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