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Parameter estimation in nonlinear stochastic models by spectral matching is studied. Models with a measured output and both known and unknown inputs are considered. Simulated data is used to estimate the spectrum of the nonlinear model and two different cost functions are suggested for the matching of the spectrum. Theoretical results on convergence and parameter covariance are discussed. An identifiability...
A novel nonlinear modelling approach has been developed and implemented on Alstom gasifier using Wiener model. The linear element of the Wiener model was identified by a combined subspace state space method, which integrated MOESP (Multivariable Output-Error State Space) and N4SID (Numerical algorithms for subspace state space system identification) method in the estimation of system matrices. Then...
Atmospheric delay is one of the major error sources in In-SAR, hindering the accurate monitoring of ground motion. Here we use the WRF (Weather Research and Forecasting) weather model to hindcast atmospheric delays at SAR acquisition times over both mountainous and flat regions. The performance of the model is evaluated by comparing it to interferograms formed using acquisitions with short temporal...
In this paper, we study bandwidth management of a wireless/optical based access/metro network in support of voice and data services. For voice services, we use a finite state Markov Chain to estimate the blocking probability of voice circuits over an Adaptive modulation and coding wireless channel, as a function of the channel parameters. For data services, we evaluate a rate matching and a buffer...
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