An overview of system modeling and identification

Abstract : System identification consists in building mathematical models of dynamical systems from experimental data. Such a methodology was mainly developed for designing model-based control systems. More generally, parameter estimation is at the heart of many signal processing applications aiming to extract information from signals, like radar, sonar, seismic, speech, communication, or biomedical (EEG, ECG, EMG) signals. Nowadays, dynamical models and identification methods play an important role in most of scientific disciplines such as automatic control, signal processing, physics, economics, medicine, biology, ecology, seismology, etc. In this plenary talk, an overview of the principal models and identification methods will be presented.
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Communication dans un congrès
11th International conference on Sciences and Techniques of Automatic control & computer engineering (STA'2010), Dec 2010, Monastir, Tunisia
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Gérard Favier. An overview of system modeling and identification. 11th International conference on Sciences and Techniques of Automatic control & computer engineering (STA'2010), Dec 2010, Monastir, Tunisia. <hal-00718864>

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