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.

SLICOT Toolboxes for MATLAB are subject to a license fee and require an individual license agreement.Find detailed information here or contact the This email address is being protected from spambots. You need JavaScript enabled to view it. directly.

Vasile Sima,  February 2, 2005