User`s guide

Identifying State-Space Models
- “How to Estimate State-Space Models with Structured Parameterization”
on page 3-93
•
Focus —Specifies the frequency-w eighing of the noise model during
estimation. See “Options for Frequency-Weighing Focus” on page 3-100.
•
DisturbanceModel —Specifies to estimate or omit the noise model for
time-domain data. See “K Matrix” on page 3-89.
•
InitialStates —Specifies to set or estimat e the initi al states. See
“Options for Initial States” on page 3-101.
For more information about these properties, see the
idss reference page.
Choosing to Estimate D, K, and X0 Matrices
For state-space models with any param eterization, you can specify whether
to estimate the K and X0 m atrices, which repre sent the noise model and the
initial states, respectively.
For state-space models with structured parameterization, you can also specify
to estimate the D matrix. Ho we ver, for free and canonical forms, the structure
of the D matrix is set based on your choice of
nk.
For m ore information about state-space structure, see “What Are State-Space
Models?” on page 3-73.
DMatrix.By default, the D matrix is not estimated. Set the model property
nk to estimate the D matrix, as follows:
• To estimate the kth column of D (corresponding to the kth input), set
nk to
0. For
nu inputs, nk is a 1-by-nu vector.
• To estim ate the full D matrix, set all
nk values to 0. For e xa m p le, for two
inputs:
m = pem(Data,n,'nk',[0 0])
To om it estimating the D matrix, set the nk value or values to 1, which is
the default.
KMatrix. K represents the noise model.
3-89