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System identification of continuous-time model based on discrete-time data can be performed using a algorithm combining linear regression and LQG-balanced model reduction. The approach is applicable also to unstable system dynamics and it provides balanced models for optimal linear prediction and control.
Asthma and rhinitis often co-exist in the same patient. Although some authors observed a higher prevalence and/or greater severity of asthma in patients with rhinitis, this view is not homogeneous and the debate continues. The aim of our study is to describe the prevalence of rhinitis in children and adolescents and to analyse their relationship with the prevalence of asthma. A multicentre study w
Polygenic risk scores (PRS) for prostate cancer incidence have been proposed to optimize prostate cancer screening. Prediction of lethal prostate cancer is key to any stratified screening program to avoid excessive overdiagnosis. Herein, PRS for incident prostate cancer was evaluated in two population-based cohorts of unscreened middle-aged men linked to cancer and death registries: the Västerbott
Background: Some degree of spontaneous recovery is usually observed after stroke. Experimental studies have provided information about molecular mechanisms underlying this recovery. However, the majority of pre-clinical stroke studies are performed in male rodents, and females are not well studied. This is a clear discrepancy when considering the clinical situation. Thus, it is important to includ
This paper presents theory, algorithms and validation results for system identification of continuous-time state-space models from finite non-uniformly sampled input-output sequences. The algorithms developed are methods of model identification and stochastic realization adapted to the continuous-time model context using non-uniformly sampled input-output data. The resulting model can be decompose
This study explores how democracy—often understood as an abstract concept or a location- transcending, intangible phenomenon—is produced, shaped and continuously reshaped through local library practices in certain places and under local conditions at a specific point in time. To better understand potential conflicts and/or tensions that might arise between the three levels of Swedish library polic
This paper offers a two-zone, physical, NOx model with low computational cost, implemented in C on an embedded system. The model is able to compute NOx-emission formation with high time resolution during an engine cycle. To do this the model takes cylinder pressure and injected fuel amount as inputs and produces NO concentration as output. The model as such is not new, nevertheless the physical ba
The paper describes an on-line identification algorithm to estimate the steam production of a municipal solid waste incinerator. The algorithm has to learn on-line the system dynamics due to the heavy disturbances acting on the incineration process. The learning algorithm is based on radial basis function networks and combines the growth criterion of the resource allocating network technique with
Bakgrund: I samband med en workshop om att jobba i lärplattformen Canvas så inledde tre bibliotekarie vid Lunds universitet ett projekt att skapa en resurs för referenshanteringsprogrammet EndNote. Vi började i januari 2020 och lanserade vår Canvas-kurs med EndNote X9 i augusti 2020. Under 2021 uppdaterades hela kursen för att anpassas till EndNote 20.Syfte: Syftet var att täcka en lucka, då vi sa
Recursive estimation in feedback operation as used in minimum variance adaptive control is considered. The paper uses Lyapunov theory and supermartingale analysis to is to remove the stochastic stability assumption in previous work.
