A Position-Tracking Method for Arc Motor Based on Iterative Learning Super-Twisting Observer and Super-Twisting Control
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Journal of Emerging and Selected Topics in Power Electronics"
DOI: 10.1109/jestpe.2024.3509137
Abstract: This article introduces a method focused on enhancing the position-tracking performance of permanent magnet arc motors (PMAMs) through the implementation of iterative learning super-twisting observer and super-twisting control (ILSTO-STC). The primary control objective is to… read more here.
Keywords: control; position; super twisting; iterative learning ... See more keywords
E2SRI: Learning to Super-Resolve Intensity Images From Events
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"
DOI: 10.1109/tpami.2021.3096985
Abstract: An event camera reports per-pixel intensity differences as an asynchronous stream of events with low latency, high dynamic range (HDR), and low power consumption. This stream of sparse/dense events limits the direct use of well-known… read more here.
Keywords: e2sri learning; event; event camera; learning super ... See more keywords
Improving Clinical Utility of Fetal Cine CMR Using Deep Learning Super-Resolution.
Sign Up to like & getrecommendations! Published in 2025 at "Circulation. Cardiovascular imaging"
DOI: 10.1161/circimaging.125.018090
Abstract: BACKGROUND Fetal cardiovascular magnetic resonance is an emerging tool for prenatal congenital heart disease assessment, but long acquisition times and fetal movements limit its clinical use. This study evaluates the clinical utility of deep learning… read more here.
Keywords: deep learning; cine; clinical utility; resolution ... See more keywords