24 papers · ranked by Valyu relevance
Daniel Medina, Haoqing Li, Jordi Vilà-Valls, Pau Closas + 1 more
'Jaume Sanz Subirana'] Global navigation satellite systems (GNSSs) play a key role in intelligent transportation systems such as autonomous driving or unmanned systems navigation. In such applications, it is fundamental to ensure a reliable precise positioning solution able to operate in harsh propagation conditions…
Yu Yifan, Xiu, Shengjie, Palomar + 1 more
—State-space models are pivotal for dynamic system analysis but often struggle with outlier data that deviates from Gaussian distributions, frequently exhibiting skewness and heavy tails. This paper introduces a robust extension utilizing the asymmetric Laplace distribution, specifically tailored to capture these…
Mattia Zorzi
We consider a family of divergence-based minimax approaches to perform robust filtering. The mismodeling budget, or tolerance, is specified at each time increment of the model. More precisely, all possible model increments belong to a ball which is formed by placing a bound on the Tau-divergence family between the…
Thomas Kautz, Bjoern M. Eskofier, Stefano Mariani
The Kalman filter (KF) is an extremely powerful and versatile tool for signal processing that has been applied extensively in various fields. We introduce a novel Kalman-based analysis procedure that encompasses robustness towards outliers, Kalman smoothing and real-time conversion from non-uniformly sampled inputs to…
Muhammad Adeel Akram, Peilin Liu, Muhammad Owais Tahir, Waqas Ali + 1 more
'Yuze Wang'] Consistent state estimation is a vital requirement in numerous real life applications from localization to multi-source information fusion. The Kalman filter and its variants have been successfully used for solving state estimation problems. Kalman filtering-based estimators are dependent upon system model…
Chen Jiang, Shu-Bi Zhang
As an optimal estimation method, the Kalman filter is the most frequently-used data fusion strategy in the field of dynamic navigation and positioning. Nevertheless, the abnormal model errors seriously degrade performance of the conventional Kalman filter. The adaptive Kalman filter was put forward to control the…
Hongwei Wang, Hongbin Li, Wei Zhang, Junyi Zuo + 1 more
We consider the problem of robust estimation involving filtering and smoothing for nonlinear state space models which are disturbed by heavy-tailed impulsive noises. To deal with heavy-tailed noises and improve the robustness of the traditional nonlinear Gaussian Kalman filter and smoother, we propose in this work a…
Hongwei Wang, Wei Zhang, Junyi Zuo, Heping Wang
We consider the robust filtering problem for a nonlinear state-space model with outliers in measurements. To improve the robustness of the traditional Kalman filtering algorithm, we propose in this work two robust filters based on mixture correntropy, especially the double-Gaussian mixture correntropy and…
Alexei V. Nikitin, Ruslan L. Davidchack
—Robust fencing is an essential component of intermittently nonlinear filtering for mitigation of outlier interference. In such filtering, the upper and the lower fences establish a robust range that excludes noise outliers while including the signal of interest and the non-outlier noise. Then, the outlier values are…
Aamir Hussain Chughtai, Muhammad Tahir, Momin Uppal
—In this article, we consider the problem of outlierrobust state estimation where the measurement noise can be correlated. Outliers in data arise due to many reasons like sensor malfunctioning, environmental behaviors, communication glitches, etc. Moreover, noise correlation emerges in several realworld applications…
Shibdas Roy, Dominic W. Berry, Ian R. Petersen, Elanor H. Huntington
Quantum parameter estimation plays a key role in many fields like quantum computation, communication and metrology. Optimal estimation allows one to achieve the most precise parameter estimates, but requires accurate knowledge of the model. Any inevitable uncertainty in the model parameters may heavily degrade the…
Viljami Sairanen, Mario Ocampo-Pineda, Cristina Granziera, Simona Schiavi + 1 more
The white matter structures of the human brain can be represented using diffusion-weighted MRI tractography. Unfortunately, tractography is prone to find false-positive streamlines causing a severe decline in its specificity and limiting its feasibility in accurate structural brain connectivity analyses. Filtering…
Jaline Gerardin, Wendell A. Lim
Many cellular responses for which timing is critical display temporal filtering – the ability to suppress response until stimulated for longer than a given minimal time. Temporal filtering can play a key role in filtering noise, choreographing the timing of events, and mediating the interpretation of dynamically…
Joram van Driel, Christian N.L. Olivers, Johannes J. Fahrenfort
Traditionally, EEG/MEG data are high-pass filtered and baseline-corrected to remove slow drifts. Minor deleterious effects of high-pass filtering in traditional time-series analysis have been well-documented, including temporal displacements. However, its effects on time-resolved multivariate pattern classification…
Wenjuan Qi, Shigang Wang, Youqiang Xing, Xiuqing Hao + 1 more
This paper addresses the robust Kalman filtering problem for multisensor time-varying systems with uncertainties of noise variances. Using the minimax robust estimation principle, based on the worst-case conservative system with the conservative upper bounds of noise variances, the robust local time-varying Kalman…
Alain de Cheveigné, Dorothée Arzounian
Electroencephalography (EEG), magnetoencephalography (MEG) and related techniques are prone to glitches, slow drift, steps, etc., that contaminate the data and interfere with the analysis and interpretation. These artifacts are usually addressed in a preprocessing phase that attempts to remove them or minimize their…
Shaolin Hu, Xianxi Chen, Guoxi Sun
This paper presents a sliding window constrained fault-tolerant filtering method for sampling data in petrochemical instrumentation. The method requires the design of an appropriate sliding window width based on the time series, as well as the expansion of both ends of the series. By utilizing a sliding window…
Authors not listed
This study presents a validation and refinement of the “yellow cards” error detection workflow that can be applied to any property connected to molecular structure. In our implementation the workflow employed 5 predictive models with each assigning a “yellow card” to 5% of the entries with worst prediction accuracy.…
Zhe Li, Josue Ortega Caro, Evgenia Rusak, Wieland Brendel + 5 more
Machine learning models have difficulty generalizing to data outside of the distribution they were trained on. In particular, vision models are usually vulnerable to adversarial attacks or common corruptions, to which the human visual system is robust. Recent studies have found that regularizing machine learning models…
Authors not listed
Graph Neural Networks (GNNs) are powerful tools for molecular property prediction, but they are not magic. When applied to molecules unlike their training data, they produce unreliable predictions that are difficult to detect. The Applicability Domain (AD) concept addresses this by defining regions of chemical space…
Baptiste Py, Adeleke Maradesa, Francesco Ciucci
Electrochemical impedance spectroscopy (EIS) is a widespread characterization technique used to study electrochemical systems. However, several shortcomings still limit the application of this technique. First, EIS data is intrinsically noisy, hindering spectra regression and prediction at unknown frequencies. Second…
Althea Hansel-Harris, Andreas Tillack, Diogo Santos-Martins, Matthew Holcomb + 1 more
Virtual screening using molecular docking is now routinely used for the rapid evaluation of very large ligand libraries. As such, it has become an increasingly common approach in early-stage drug discovery. These screenings generate large amounts of data proportional to the size of the compound library used, which must…
Authors not listed
For the first time a printable, miniaturized and gate-controlled electrochemical capacitor-diode (G-CAPode) is presented. The heart of the device consists of a recently developed asymmetric electrical double-layer capacitor system based on selective, size-depended ion adsorption. Due to the introduction of a sieving…
Authors not listed
Scanning emission-based microscopies, such as X-ray fluorescence (XRF) and energy-dispersive X-ray spectroscopy, offer nanometer-scale chemical maps, but suffer from long acquisition times and radiation damage. Lower-flux and shorter dwell time scans mitigate this problem, but the resulting signal loss can only…