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This paper serves as a first identification step in a two-step model-based control synthesis problem of switched linear systems (SLSs). More precisely, we present an algorithm that addresses the realization of the multi-input/multi-output MIMO-SLSs from Markov parameters under mild assumptions on the dwell-times and the submodels. A key point of the proposed approach is the introduction of the for
In this paper, we propose a framework to iden-tify discrete-time, multi-input/multi-output (MIMO), switched-linear systems (SLSs) from input-output data. The key step is an observer-based transformation to a switched auto-regressive with exogenous input (SARX) model. This transformation has a nontrivial kernel complicating identification, but converts the state-space identification problem to SARX
It is well known that reformulating the original problem can be crucial for the performance of mixed-integer programming (MIP) solvers. To ensure correctness, all transformations must preserve the feasibility status and optimal value of the problem, but there is currently no established methodology to express and verify the equivalence of two mixed-integer programs. In this work, we take a first s
In the last couple of decades, developments in SAT-based optimization have led to highly efficient maximum satisfiability (MaxSAT) solvers, but in contrast to the SAT solvers on which MaxSAT solving rests, there has been little parallel development of techniques to prove the correctness of MaxSAT results. We show how pseudo-Boolean proof logging can be used to certify state-of-the-art core-guided
Safety measures need to be systemically investigated to what extent they evaluate the intended performance of Deep Neural Networks (DNNs) for critical applications. Due to a lack of verification methods for high-dimensional DNNs, a trade-off is needed between accepted performance and handling of out-of-distribution (OOD) samples.This work evaluates rejecting outputs from semantic segmentation DNNs
There are many pedagogical methods to engage students in active learning. This paper presents Discussion Seminars, which is one such method that is much appreciated by students. This paper explains how to structure seminars and discusses their benefits and what requirements they put on the teacher. The paper aims to inspire other teachers to try something similar.
A Brain-Computer Interface (BCI) is a system that, in real-time, translates the user's brain activity into commands that can be used to control applications, such as moving a cursor on the screen. The translation is made possible by machine learning methods and other algorithms. The thesis focuses on EEG-based BCIs which are the most common type of BCIs due to EEG measurements being non-invasive,
A recent singleshot multiplane image (MPI) generation enables to copy an observed reality within a camera frame into other reality domains via view synthesis. While the scene scale is unknown due to the nature of singleshot MPI processing, camera tracking algorithms can estimate depth within the application world coordinate system. Given such depth information, we propose to adjust the scale of si
We propose a variation of the forward–backward splitting method for solving structured monotone inclusions. Our method integrates past iterates and two deviation vectors into the update equations. These deviation vectors bring flexibility to the algorithm and can be chosen arbitrarily as long as they together satisfy a norm condition. We present special cases where the deviation vectors, selected
The geometry-based stochastic channel models (GSCM), which can describe realistic channel impulse responses, often rely on the existence of both local and far scatterers. However, their visibility from both the base station (BS) and mobile station (MS) depends on their relative heights and positions. For example, the condition of visibility of a scatterer from the perspective of a BS is different
We study optimal seeding problems for binary super-modular network games. The system planner's objective is to design a minimal cost seeding guaranteeing that at least a predefined fraction of the players adopt a certain action in every Nash equilibrium. Since the problem is known to be NP-hard and its exact solution would require full knowledge of the network structure, we focus on approximate so
This article considers state estimation of rigid-body dynamics where the positions q are available to measurement but where the angular velocities ̇or accelerations are not available to measurement. Using a stability-oriented approach to model-based design of state estimation for Euler–Lagrange systems and rigid-body dynamics, state estimation based on position measurement is shown to guarantee se
After the COVID-19 pandemic, during which teachers developed a lot of online course material, teachers worldwide are challenged with how to combine online teaching with classroom teaching in an efficient way. This paper presents Discussion seminars, a teaching activity that structures discussions clearly, making it easy for students and teachers to follow the discussion. The paper puts Discussion
Effective preprocessing of electroencephalography (EEG) data is fundamental for deriving meaningful insights. Independent component analysis (ICA) serves as an important step in this process by aiming to eliminate undesirable artifacts from EEG data. However, the decision on which and how many components to be removed remains somewhat arbitrary, despite the availability of both automatic and manua
The wide spread of on-line social networks poses new challenges in information environment and cybersecurity. A key issue is detecting stubborn behaviors to identify leaders and influencers for marketing purposes, or extremists and automatic bots as potential threats. Existing literature typically relies on known network topology and extensive centrality measures computation. However, the size of
In this thesis, we provide a number of novel algebraic means of certifying stability and performance for linear systems constrained in various ways by cones. The purpose is mainly threefold: to provide mathematical statements with applicative potential, to unify seemingly dissimilar results in the literature and thereby increase understanding, and to advance the state of the art on dynamical syste
The analysis of interconnected systems is a large and growing field, with successful applications in a wide range of natural and synthesized systems. Biomolecular networks, power grids and human social dynamics have all been the subject of study through the lens of network dynamics, with impressive results. The work presented in this thesis takes the form of four research papers all focusing in di
LU-PZE is an interactive tool for illustrating fundamental concepts related to control theory, covering the relation between transfer functions, pole-zero plots, step responses, Bode plots, and Nyquist diagram. The tool gamifies education with dynamic assignments and quizzes. The tool is straightforward to use since it is web-based. https://lu-pze.github.io
The enhancement and protection of coastal ecosystems that sequester carbon for climate change mitigation have developed over the last 15 years, and today are part of climate governance. After an initially challenging start in terms of policy interest, Blue Carbon is now included in some countries’ national inventories, and as such, enters the global sums of emissions and sinks, and becomes relevan
This thesis discusses novel results in the area of code-based cryptography, ranging from cryptanalyses on several code-based cryptographic constructions to proposing a code-based authentication scheme based on a novel Syndrome Decoding variant.To address the looming threat of large-scale quantum computers that wouldbreak many widely-used public-key cryptosystems, the National Institute of Stan-dar
