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SLICOT System Identification Toolbox
- SLICOT
System Identification Toolbox includes SLICOT-based MATLAB and
Fortran
tools for linear and Wiener-type, time-invariant discrete-time
multivariable systems. Subspace-based approaches MOESP -
Multivariable
Output-Error state SPace identification, N4SID - Numerical
algorithms for Subspace State Space System IDentification, and
their
combination, are used to identify linear systems, and to initialize the
parameters of the linear part of a Wiener system. All parameters of a
Wiener system are then estimated using a specialized
Levenberg-Marquardt algorithm.
- The
main functionalities of the toolbox
include:
- identification
of linear discrete-time state space systems (A, B, C, D)
- identification
of state and output (cross-)covariance matrices for such
systems
- estimation
of the associated Kalman gain matrix
- estimation
of the initial state
- conversion
from/to a state-space representation to/from the output normal
form parameterization
- identification of discrete-time Wiener systems
- computation
of the output response of Wiener systems.
The
toolbox
main features are:
- computational reliability
- high numerical efficiency, using structure exploiting algorithms
and dedicated linear algebra tools
- possible speed-up factors larger then 10 in comparison with the
commonly used software tools
- flexibility and easy-of-use
- ability to process multiple (possibly connected) data batches
- standardized interfaces
The
programs have
been extensively tested on various test
examples and are fully documented.
Vasile
Sima, February 2, 2005
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