Related papers: Fisher-Information-Based Sensor Placement for Stru…
All-pairs set similarity is a widely used data mining task, even for large and high-dimensional datasets. Traditionally, similarity search has focused on discovering very similar pairs, for which a variety of efficient algorithms are known.…
One of the challenges of predictive maintenance is making decisions based on data in an agile and assertive way. Connected sensors and operational data favor intelligent processing techniques to enrich information and enable…
We propose a \textit{guided multi-fidelity Bayesian optimization} framework for data-efficient controller tuning that integrates corrected digital twin simulations with real-world measurements. The method targets closed-loop systems with…
Optimal sensor placement is a central challenge in the design, prediction, estimation, and control of high-dimensional systems. High-dimensional states can often leverage a latent low-dimensional representation, and this inherent…
Reconfigurable intelligent surfaces (RISs) are envisioned to play a key role in future wireless communication networks. However, channel estimation in RIS-aided wireless networks is challenging due to their passive nature and the large…
Wireless sensor networks consist of sensor nodes that are physically distributed over different locations. Spatial filtering procedures exploit the spatial correlation across these sensor signals to fuse them into a filtered signal…
Digital Twins promise to deliver a step-change in distribution system operations and planning, but there are few real-world examples that explore the challenges of combining imperfect model and measurement data, and then use these as the…
Sensor placement for linear inverse problems is the selection of locations to assign sensors so that the entire physical signal can be well recovered from partial observations. In this paper, we propose a fast sampling algorithm to place…
The current fusion positioning systems are mainly based on filtering algorithms, such as Kalman filtering or particle filtering. However, the system complexity of practical application scenarios is often very high, such as noise modeling in…
The essential of navigation, perception, and decision-making which are basic tasks for intelligent robots, is to estimate necessary system states. Among them, navigation is fundamental for other upper applications, providing precise…
This paper proposes a novel localization algorithm using the reconfigurable intelligent surface (RIS) received signal, i.e., RIS information. Compared with BS received signal, i.e., BS information, RIS information offers higher dimension…
This chapter provides an introduction to the foundations of digital twins and makes the case for employing them in smart grids. As engineered systems become more complex and autonomous, digital twin technology gains importance as the…
Assimilation of continuously streamed monitored data is an essential component of a digital twin; the assimilated data are used to ensure the digital twin is a true representation of the monitored system. One way this is achieved is by…
Consider the two related problems of sensor selection and sensor fusion. In the first, given a set of sensors, one wishes to identify a subset of the sensors, which while small in size, captures the essence of the data gathered by the…
Insufficient data volume and quality are particularly pressing challenges in the adoption of modern subsymbolic AI. To alleviate these challenges, AI simulation uses virtual training environments in which AI agents can be safely and…
We consider estimating the magnitude of a monochromatic AC signal that couples to a two-level sensor. For any detection protocol, the precision achieved depends on the signal's frequency and can be quantified by the quantum Fisher…
One of the key challenges in performing muon experiments is knowing which temperatures and applied fields to measure at, and how many muon decays should be measured at each temperature/field combination to get the most useful dataset. We…
Large-dimensional empirical data in science and engineering frequently have a low-rank structure and can be represented as a combination of just a few eigenmodes. Because of this structure, we can use just a few spatially localized sensor…
Industrial process optimization and control is crucial to increase economic and ecologic efficiency. However, data sovereignty, differing goals, or the required expert knowledge for implementation impede holistic implementation. Further,…
The Digital Twins offer promising solutions for smart grid challenges related to the optimal operation, management, and control of energy assets, for safe and reliable distribution of energy. These challenges are more pressing nowadays than…