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ARMASA features a unique program to estimate the power spectrum. The spectrum containing all significant details is calculated from a time series model. Model type as well as model order are determined automatically from the data, using statistical criteria. Robust estimation algorithms and order selection criteria are used to obtain reliable results. Unlike in FFT analysis, where the experimenter has to set the amount of smoothing of the raw FFT, the right level of detail is assessed using the data only.

Any part of the ARMASA software package may freely be used for scientific or educational purposes.

P.M.T. Broersen, Automatic Spectral Analysis with Time Series Models,
IEEE Transactions on Instrumentation and Measurement,
Vol. 51, No. 2, April 2002, pp. 211-216.

For questions contact P.M.T. Broersen



This is the second release of the closed-loop identification toolbox CLOSID.

For questions contact P.M.J. Van den Hof



The software is shareware and can be used to estimate or identify linear time invariant (multivariable) models on the basis of frequency domain response measurements. The FREQID toolbox is equipped with a GUI (Grafical User Interface) to simplify both the manipulation of frequency domain data, the choice of the weighting functions and the model order selection during the estimation of a model.

For questions contact R.A. de Callafon


gPROMS models

used in "Model Reduction for Dynamic Real-Time Optimization of Chemical Processes" by Jogchem van den Berg

For questions contact Jogchem van den Berg



ORTTOOL is a Matlab Toolbox for System Identification with generalized orthonormal basis functions.
It is primarily constructed for PC-platforms. If you are using another platform, please read the file mexsource.

For questions contact dr. P.S.C. Heuberger



For questions contact P.M.J. Van den Hof



WOR s a Matlab Toolbox for frequency-weighted balanced model reduction. The zip-file also contains a user guide in ps-format.

For questions contact O.H. Bosgra

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Last modified: 7 December 2005, 9:59 UTC
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