Related papers: Feed-forward active magnetic shielding
In this work a design is proposed for an active, permanent magnet based, self-propelled magnetic bearing i.e. levitating motor having the following features : (a) simple winding structure, (b) high load supporting capacity, (c) no…
Algorithms that exploit factored Markov decision processes are far more sample-efficient than factor-agnostic methods, yet they assume a factored representation is known a priori -- a requirement that breaks down when the agent sees only…
An experimental strong increase of the reflection loss (from 25 up to 35 dBs) and an extension of the absorption bandwidth up to 20% is measured in a set of novel functional bilayer systems. We focus our work on studying the samples in an…
A core goal of functional neuroimaging is to study how the environment is processed in the brain. The mainstream paradigm involves concurrently measuring a broad spectrum of brain responses to a small set of environmental features…
We present a target field approach to analytically design magnetic fields using permanent magnets. We assume that their magnetisation is bound to a two-dimensional surface and is composed of a complete basis of surface modes. By posing the…
Because they represent physical systems with propagation delays, hyperbolic systems are well suited for feedforward control. This is especially true when the delay between a disturbance and the output is larger than the control delay. In…
Fully Depleted Monolithic Active Pixels (FD-MAPS) represent a state-of-the-art detector technology and profit from a low material budget and cost for high energy physics experiments and other fields of research like medical imaging and…
Near-field technologies enable contactless payments, building access, automotive keyless entry, and supply chain tracking. Existing approaches face fundamental trade-offs: magnetic-based methods (NFC/NFMI) achieve low power but are limited…
A versatile and portable magnetically shielded room with a field of (700 \pm 200) pT within a central volume of 1m x 1m x 1m and a field gradient less than 300 pT/m is described. This performance represents more than a hundred-fold…
Modern MIMO communication systems are almost exclusively designed under the assumption of locally plane wavefronts over antenna arrays. This is known as the far-field approximation and is soundly justified at sub-6-GHz frequencies at most…
Spin preparation prior to a free-induction-decay (FID) measurement can be adversely affected by transverse bias fields, particularly in the geophysical field range. A strategy that enhances the spin polarization accumulated before readout…
Mobile and embedded machine learning developers frequently have to compromise between two inferior on-device deployment strategies: sacrifice accuracy and aggressively shrink their models to run on dedicated low-power cores; or sacrifice…
Recently, self-attention models such as Transformers have given competitive results compared to recurrent neural network systems in speech recognition. The key factor for the outstanding performance of self-attention models is their ability…
Metasurface antenna arrays, formed by tiling multiple metasurface subapertures, offer an alternative architecture to electrically large beamsteering arrays often used in radar and communications. The advantages offered by metasurfaces are…
Scalar optically-pumped magnetometers (OPMs) are being developed in small packages with high sensitivities. The high common-mode rejection ratio of these sensors allows for detection of very small signals in the presence of large background…
Active learning is a practical field of machine learning that automates the process of selecting which data to label. Current methods are effective in reducing the burden of data labeling but are heavily model-reliant. This has led to the…
Optical aberrations prevent telescopes from reaching their theoretical diffraction limit. Once estimated, these aberrations can be compensated for using deformable mirrors in a closed loop. Focal plane wavefront sensing enables the…
Active noise control typically employs adaptive filtering to generate secondary noise, where the least mean square algorithm is the most widely used. However, traditional updating rules are linear and exhibit limited effectiveness in…
Safe exploration is a common problem in reinforcement learning (RL) that aims to prevent agents from making disastrous decisions while exploring their environment. A family of approaches to this problem assume domain knowledge in the form…
Deep neural networks employing error back-propagation for learning can suffer from exploding and vanishing gradient problems. Numerous solutions have been proposed such as normalisation techniques or limiting activation functions to linear…