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Dynamic factor models are often estimated by point-estimation methods, disregarding parameter uncertainty. We propose a method accounting for parameter uncertainty by means of posterior approximation, using variational inference. Our…

Methodology · Statistics 2022-10-14 Erik Spånberg

Tool flank wear monitoring can minimize machining downtime costs while increasing productivity and product quality. In some industrial applications, only a limited level of tool wear is allowed to attain necessary tolerances. It may become…

Signal Processing · Electrical Eng. & Systems 2022-12-29 D. Bilgili , G. Kecibas , C. Besirova , M. R. Chehrehzad , G. Burun , T. Pehlivan , U. Uresin , E. Emekli , I. Lazoglu

Noise measurement on a population of gearbox manufactured in large number often reveals high variability due to tolerances on each gear design parameter (manufacturing errors). Gearbox noise results mainly from housing vibration induced by…

Classical Physics · Physics 2016-08-14 N. Driot , Emmanuel Rigaud , Joël Perret-Liaudet

The precise control of soft and continuum robots requires knowledge of their shape, which has, in contrast to classical rigid robots, infinite degrees of freedom. To partially reconstruct the shape, proprioceptive techniques use built-in…

High performance trajectory tracking control of quadrotor vehicles is an important challenge in aerial robotics. Symmetry is a fundamental property of physical systems and offers the potential to provide a tool to design high-performance…

Robotics · Computer Science 2022-11-23 Matthew Hampsey , Pieter van Goor , Tarek Hamel , Robert Mahony

Stably inverting a dynamic system model is the foundation of numerous servo designs. Existing inversion techniques have provided accurate model approximations that are often highly effective in feedforward controls. However, when the…

Systems and Control · Computer Science 2019-11-19 Dan Wang , Xu Chen

For a high-dimensional linear model with a finite number of covariates measured with error, we study statistical inference on the parameters associated with the error-prone covariates, and propose a new corrected decorrelated score test and…

Methodology · Statistics 2020-01-29 Mengyan Li , Runze Li , Yanyuan Ma

The quality of tool paths is a dominant factor in CNC machining, determining its efficiency and accuracy. This paper provides a brief review (in Chinese) on tool path planning methods reported in the literature, focusing on their…

Other Computer Science · Computer Science 2022-12-16 Qiang Zou

Superresolution theory and techniques seek to recover signals from samples in the presence of blur and noise. Discrete image registration can be an approach to fuse information from different sets of samples of the same signal. Quantization…

Computer Vision and Pattern Recognition · Computer Science 2024-12-16 Serap A. Savari

A change point problem occurs in many statistical applications. If there exist change points in a model, it is harmful to make a statistical analysis without any consideration of the existence of the change points and the results derived…

Methodology · Statistics 2011-01-24 Xiaoping Shi , Yuehua Wu , Baisuo Jin

Linear Hall sensors are a cost-effective alternative to optical encoders for measuring the rotor positions of actuators, with the main challenge being that they exhibit position-dependent inaccuracies resulting from manufacturing…

Systems and Control · Electrical Eng. & Systems 2025-05-08 Max van Meer , Marijn van Noije , Koen Tiels , Enzo Evers , Lennart Blanken , Gert Witvoet , Tom Oomen

High-dimensional vector autoregression with measurement error is frequently encountered in a large variety of scientific and business applications. In this article, we study statistical inference of the transition matrix under this model.…

Methodology · Statistics 2020-09-18 Xiang Lyu , Jian Kang , Lexin Li

Robot positioning accuracy is a key factory when performing high-precision manufacturing tasks. To effectively improve the accuracy of a manipulator, often up to a value close to its repeatability, calibration plays a crucial role. In the…

Robotics · Computer Science 2025-02-24 Giovanni Boschetti , Teresa Sinico

This paper investigates the asymptotic behavior of the soft-margin and hard-margin support vector machine (SVM) classifiers for simultaneously high-dimensional and numerous data (large $n$ and large $p$ with $n/p\to\delta$) drawn from a…

Information Theory · Computer Science 2020-03-31 Abla Kammoun , Mohamed-Slim Alouini

Mobile manipulators consist of a mobile platform equipped with one or more robot arms and are of interest for a wide array of challenging tasks because of their extended workspace and dexterity. Typically, mobile manipulators are deployed…

Robotics · Computer Science 2020-03-18 Ke Dong , Karime Pereida , Florian Shkurti , Angela P. Schoellig

In computed tomography (CT), the relative trajectories of a sample, a detector, and a signal source are traditionally considered to be known, since they are caused by the intentional preprogrammed movement of the instrument parts. However,…

Computer Vision and Pattern Recognition · Computer Science 2021-11-11 Mark Griguletskii , Mikhail Chekanov , Oleg Shipitko

Background Analyzing kinematic and video data can help identify potentially erroneous motions that lead to sub-optimal surgeon performance and safety-critical events in robot-assisted surgery. Methods We develop a rubric for identifying…

Robotics · Computer Science 2023-01-20 Kay Hutchinson , Zongyu Li , Leigh A. Cantrell , Noah S. Schenkman , Homa Alemzadeh

The most critical component of any adaptive numerical quadrature routine is the estimation of the integration error. Since the publication of the first algorithms in the 1960s, many error estimation schemes have been presented, evaluated…

Numerical Analysis · Computer Science 2010-11-09 Pedro Gonnet

A growing number of wind turbines are equipped with vibration measurement systems to enable a close monitoring and early detection of developing fault conditions. The vibration measurements are analyzed to continuously assess the component…

Machine Learning · Computer Science 2022-02-17 Angela Meyer

Transformers are widely used deep learning architectures. Existing transformers are mostly designed for sequences (texts or time series), images or videos, and graphs. This paper proposes a novel transformer model for massive (up to a…

Machine Learning · Computer Science 2023-11-09 Wenchong He , Zhe Jiang , Tingsong Xiao , Zelin Xu , Shigang Chen , Ronald Fick , Miles Medina , Christine Angelini
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