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In this paper, we consider near-field localization and sensing with an extremely large aperture array under partial blockage of array antennas, where spherical wavefront and spatial non-stationarity are accounted for. We propose an Ising model to characterize the clustered sparsity feature of the blockage pattern, develop an algorithm based on alternating optimization for joint channel parameter e
Background: Markov models are models used to describe movement of individuals between states. In medicine, Markov models are used to describe, for example, disease progression and the effects of interventions on such progression. The models can further be used to identify medical risk groups and aid clinicians in clinical decision making. Although accurate individual predictions are crucial for ut
Covariate modeling provides individual predictions of outcomes by disease progression models. Current methodology for mapping covariates onto model parameters is limited by predefined parametric functions which can result in inadequate covariate selection and biased predictions by the final model. Furthermore, present methodology scales poorly to high-dimensional data due to combinatorial limitati
Electric power systems are undergoing significant transformations as more sectors in society are electrified and new electric power generation from solar and wind is added to the grid. The growing share of renewable generation is expected to influence the dynamic behaviour of power systems, creating a need to develop new control strategies for power systems. This thesis investigates robust and opt
Strain and interactions at grain boundaries during solid-phase crystallization are known to play a significant role in the functional properties of polycrystalline materials. However, elucidating three-dimensional nanoscale grain morphology, kinetics, and strain under realistic conditions is challenging. Here, we image a single-grain growth during the amorphous-to-polycrystalline transition in tec
For linear time-invariant systems with uncertain parameters belonging to a finite set, we present a purely eterministic approach to multiple-model estimation and propose an algorithm based on the minimax criterion using constrained quadratic programming. The estimator tends to learn the dynamics of the system, and once the uncertain parameters have been sufficiently estimated, the estimator behave
Weakly-hard models have been used to analyse real-time systems subject to patterns of deadline hits and misses. However, the tools that are available in the literature have a set of shortcomings. The analysis they offer is limited to a single weaklyhard constraint and to patterns that specify the number of misses, rather than the number of hits. Furthermore, the scalability of the tools is limited
The multi-armed bandit (MAB) problem models a decision-maker that optimizes its actions based on current and acquired new knowledge to maximize its reward. This type of online decision is prominent in many procedures of Brain-Computer Interfaces (BCIs) and MAB has previously been used to investigate, e.g., what mental commands to use to optimize BCI performance. However, MAB optimization in the co
A corpus study and a combined behavioural and neurophysiological study tested how phonetic and phonological features of the Danish creaky voice feature ‘stød’ influence predictive processing. Being associated with certain word endings, stød and its modal voice counterpart non-stød can cue upcoming speech. Stød has two phases. The first shows phonetic differences in pitch while the second, characte
This article introduces a 28-nm CMOS digitally controlled oscillator (DCO) based on eight oscillator cores, where the number of active cores can be reconfigured to be either 2, 4, 6, or 8, trading power consumption for phase noise without incurring an additional phase noise penalty. The impact of the reconfiguration pMOS switches on the phase noise performance is determined through a simple yet ri
Homogeneous Charge Compression Ignition (HCCI) is a promising but challenging combustion engine concept. The potential for good fuel economy and low emissions is high but the transient performance required for automotive applications presents a few problems still to be solved. The focus of this work is identification of the process dynamics. An ARX type model is fitted to input-output data. A meth
Homogeneous Charge Compression Ignition (HCCI) combustion lacks direct ignition timing control, instead the auto ignition depends on the operating condition. Since auto ignition of a homogeneous mixture is very sensitive to operating condition a fast combustion timing control is necessary for reliable operation, the ignition timing control design requiring appropriate models and system output vari
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
In this paper, we apply an optimal Linear Quadratic (LQ) controller, which has an inherent structure that allows for a distributed implementation, to an irrigation network. The network consists of a water reservoir and connected water canals. The goal is to keep the levels close to the set-points when farmers take out water. The LQ controller is designed using a first-order approximation of the ca
Nondestructive testing of composite materials is important in aerospace applications, and mm-wave imaging has been increasingly used for this purpose. Imaging is traditionally performed using Fourier methods, with inverse methods being an alternative. This communication presents a mm-wave imaging method with an inverse approach intended for nondestructive testing of singly curved composite panels
