arXiv subjects

Henrik Maurenbrecher

Publications and source records attributed to Henrik Maurenbrecher.

3 recordsLinked to original sources

arXiv2026

On the Removal of Artifacts of Known-Shape from Noisy Signals

A general method for the estimation and removal of quasi-periodic, artifact-like disturbances from single channel measurements is presented. The method is based on a wavelet template and data-driven template extraction from single channel, noisy signals. The method is tested on an example application in modern neurology. The method is compared to an autoencoder, trained and deployed under idealized conditions, thus acting as reference system. It is found that the proposed method yields signal estimates with median root mean squared error improvement of 33% compared to the baseline, which is 4% more than the autoencoder, while relying on fewer assumptions and parameters, and without the need for any training data.

eess.SP↗

arXiv2019

Learning a Curve Guardian for Motorcycles

Up to 17% of all motorcycle accidents occur when the rider is maneuvering through a curve and the main cause of curve accidents can be attributed to inappropriate speed and wrong intra-lane position of the motorcycle. Existing curve warning systems lack crucial state estimation components and do not scale well. We propose a new type of road curvature warning system for motorcycles, combining the latest advances in computer vision, optimal control and mapping technologies to alleviate these shortcomings. Our contributes are fourfold: 1) we predict the motorcycle's intra-lane position using a convolutional neural network (CNN), 2) we predict the motorcycle roll angle using a CNN, 3) we use an upgraded controller model that incorporates road incline for a more realistic model and prediction, 4) we design a scale-able system by utilizing HERE Technologies map database to obtain the accurate road geometry of the future path. In addition, we present two datasets that are used for training and evaluating of our system respectively, both datasets will be made publicly available. We test our system on a diverse set of real world scenarios and present a detailed case-study. We show that our system is able to predict more accurate and safer curve trajectories, and consequently warn and improve the safety for motorcyclists.

cs.CV↗

arXiv2019

Chiral anisotropic magnetoresistance of ferromagnetic helices

We investigate the anisotropic magnetoresistance (AMR) of ferromagnetic CoNi microhelices fabricated by electrodeposition and laser printing. We find that the geometry of the three-dimensional winding determines a characteristic angular and field-dependence of the AMR due to the competition between helical shape anisotropy and external magnetic field. Moreover, we show that there is an additional contribution to the AMR that scales proportionally to the applied current and depends on the helix chirality. We attribute this contribution to the self magnetic field induced by the current, which modifies the orientation of the magnetization relative to the current flow along the helix. Our results underline the interest of three-dimensional curved geometries to tune the AMR and realize tubular magnetoresistive devices.

cond-mat.mes-hall↗