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In prediction error identification, the information matrix plays a central role. Specifically, when the system is in the model set, the covariance matrix of the parameter estimates converges asymptotically, up to a scaling factor, to the inverse of the infor ...
Most infrastructure in the western world was built in the second half of the 20th century. Transportation structures, water distribution networks and energy production systems are now aging and this leads to safety and serviceability issues. In situations ...
The Probalistic Latent Semantic Indexing model, introduced by T. Hofmann (1999), has engendered applications in numerous fields, notably document classification and information retrieval. In this context, the Fisher kernel was found to be an appropriate do ...
In this thesis, we investigate methods for the practical and accurate localization of Internet performance problems. The methods we propose belong to the field of network loss tomography, that is, they infer the loss characteristics of links from end-to-en ...
This lecture describes the following topics: • Dynamic Models - Conservation of Mass (Concentration Measurements) - Conservation of Energy (Calorimetry) - Beer’s Law (Spectroscop ...
The paper presents a procedure for parameter identification along with its application to the model of a combined cycle power plant that includes the surrounding electrical network, built for the analysis of islanding maneuvers transients. The paper illust ...
Identification of kinetic models is an important task for monitoring, control and optimization of industrial processes. Robust kinetic models are often based on first principles, which describe the evolution of states – number of moles, temperature and vol ...
Based on Volterra series the work presents a novel local nonlinear model of a certain class of linear-analytic systems. The special form of the expressions for the Laplace-domain Volterra kernels of such systems is exploited to obtain an approximation stru ...
Institute of Electrical and Electronics Engineers2009
Structures can be better understood when measurement data are used to improve the modeling of structural behavior. Our capacity to interpret data depends on aspects such as the choice of model class, model parameters (and their range of possible values), a ...
Identification of kinetic models is an important task for monitoring, control and optimization of industrial processes. Kinetic models are often based on first principles, which describe the evolution of the states – numbers of moles, temperature and volum ...
