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Uncertainties in Neural Networks
In science, technology, and engineering, creating models of the environment to predict future events has always been a key component. The models could be everything from how the friction of a tire depends on the wheels slip to how a pathogen is spread throughout society. As more data becomes available, the use of data-driven black-box models becomes more attractive. In many areas they have shown promising results, but for them to be used widespread in safety-critical applications such as autonomous driving some notion of uncertainty in the prediction is required. An example of such a black-box model is neural networks (NNs). This thesis aims to increase the usefulness of NNs by presenting an...
Optimization for Learning and Control
Optimization for Learning and Control Comprehensive resource providing a masters’ level introduction to optimization theory and algorithms for learning and control Optimization for Learning and Control describes how optimization is used in these domains, giving a thorough introduction to both unsupervised learning, supervised learning, and reinforcement learning, with an emphasis on optimization methods for large-scale learning and control problems. Several applications areas are also discussed, including signal processing, system identification, optimal control, and machine learning. Today, most of the material on the optimization aspects of deep learning that is accessible for students a...
Estimation of Nonlinear Greybox Models for Marine Applications
As marine vessels are becoming increasingly autonomous, having accurate simulation models available is turning into an absolute necessity. This holds both for facilitation of development and for achieving satisfactory model-based control. When accurate ship models are sought, it is necessary to account for nonlinear hydrodynamic effects and to deal with environmental disturbances in a correct way. In this thesis, parameter estimators for nonlinear regression models where the regressors are second-order modulus functions are analyzed. This model class is referred to as second-order modulus models and is often used for greybox identification of marine vessels. The primary focus in the thesis i...
Decentralized Estimation Using Conservative Information Extraction
Sensor networks consist of sensors (e.g., radar and cameras) and processing units (e.g., estimators), where in the former information extraction occurs and in the latter estimates are formed. In decentralized estimation information extracted by sensors has been pre-processed at an intermediate processing unit prior to arriving at an estimator. Pre-processing of information allows for the complexity of large systems and systems-of-systems to be significantly reduced, and also makes the sensor network robust and flexible. One of the main disadvantages of pre-processing information is that information becomes correlated. These correlations, if not handled carefully, potentially lead to underest...
Generation Ego
Skolan idag: Lärare som inte kan genomföra en lektion eftersom eleverna inte inser poängen med lektionens innehåll. Elever som tar det som självklart att betygen ska överklagas. En läroplan som kräver att barnen, från förskoleålder, fostras i entreprenöriellt lärande. Dagens unga kallas för den mest självupptagna generationen någonsin. Varför har det blivit så och vad får det för konsekvenser? När Ana Udovic skrev en artikel om ämnet i Dagens Nyheter förstod hon att det var fler än hon som intresserade sig för frågorna. Gensvaret var enormt. Artikeln blev en av DN:s mest delade på internet 2012. Ett samhälle kan knappast fungera om dess invånare gör allt för eg...
On Motion Planning Using Numerical Optimal Control
During the last decades, motion planning for autonomous systems has become an important area of research. The high interest is not the least due to the development of systems such as self-driving cars, unmanned aerial vehicles and robotic manipulators. In this thesis, the objective is not only to find feasible solutions to a motion planning problem, but solutions that also optimize some kind of performance measure. From a control perspective, the resulting problem is an instance of an optimal control problem. In this thesis, the focus is to further develop optimal control algorithms such that they be can used to obtain improved solutions to motion planning problems. This is achieved by combi...
Tankejägaren 2.0
Tankejägaren 2.0 är en fascinerande resa in i vårt inre landskap, där tankar, minnen och medvetande samspelar på ett intrikat sätt. Detta är inte bara en bok, det är en utforskning av det mänskliga psyket. Boken börjar med en grundlig utforskning av hur våra tankar påverkar oss. Varför fastnar vi ibland i negativa tankecykler? Hur påverkar våra tankar våra känslor och beteenden? Med hjälp av exempel och insiktsfulla observationer, visar han hur vi ofta blir fångade i våra egna mentala fällor och hur detta leder till oro, ångest och hinder i att nå våra mål. En central del av boken är dess fokus på interaktionen mellan tankar och minne. Hur våra minnen formar våra...
Built on a Rock
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