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Estimate state-space model by reduction of regularized ARX model

`sys = ssregest(data,nx)`

`sys = ssregest(data,nx,Name,Value)`

`sys = ssregest(___,opt)`

`[sys,x0] = ssregest(___)`

specifies
additional options using one or more `sys`

= ssregest(`data`

,`nx`

,`Name,Value`

)`Name,Value`

pair
arguments.

`ssregest`

function provides improved accuracy than`n4sid`

for short, noisy data sets.For some problems, the quality of fit using

`n4sid`

is sensitive to options, such as`N4Horizon`

, whose values can be difficult to determine. In comparison, the quality of fit with`ssregest`

is less sensitive to its options, which makes`ssregest`

simpler to use.

`ssregest`

estimates a regularized ARX model
and converts the ARX model to a state-space model. The software then
uses balanced model reduction techniques to reduce the state-space
model to the specified order.

[1] Ljung, L. *System Identification:
Theory For the User*, Second Edition, Appendix 4A, pp 132-134,
Upper Saddle River, N.J: Prentice Hall, 1999.

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