Electrical Engineering
No mentions found
This entity hasn't been tracked yet, or Iris is still building its knowledge base.
Related Articles from SNS
Electrically tunable spin qubits in strain-engineered graphene p-n junctions
arXiv:2512.14508v2 Announce Type: replace-cross Abstract: Strain engineering enables quantum confinement in pristine graphene without degrading its intrinsic mobility and spin coherence. Here, we extend previously proposed strain-induced charge-qubit architectures by incorporating spin degrees of freedom through Rashba spin-orbit coupling (RSOC) and Zeeman fields, enabling spin-qubit operation in single-layer graphene (SLG). In a graphene p-n junction, a strain-induced nanobubble generates a...
F1 details reduced electric power unit changes for 2027 and 2028
F1 details reduced electric power unit changes for 2027 and 2028 June 10 : Formula One's governing body announced agreement on a package of rule changes to reduce the electric power element in the cars' engines in 2027 and 2028. The International Automobile Federation (FIA) said in a statement on Wednesday that the current 53-47 split between combustion engine and electric power would stretch to 58-42 in 2027 and 60-40 the following year.
How Vibhav Altekar went from just an engineer to powering a landmark US military rescue
Indian-American engineer Vibhav Altekar has come into the spotlight after a drone boat developed by his company, Saronic Technologies, played a role in a first-of-its-kind US military rescue mission near the Strait of Hormuz. Altekar studied Electrical Engineering at the University of California, Davis. During his time there, he worked on research projects in areas including machine learning, bioinformatics and materials science.
Optimal Wiener-Filter Solutions for Denoising of Graph Signals on Directed Graphs
Electrical Engineering and Systems Science > Signal Processing [Submitted on 5 Jun 2026] Title:Optimal Wiener-Filter Solutions for Denoising of Graph Signals on Directed Graphs View PDF HTML (experimental)Abstract:Graph signal processing has opened new avenues to the canonical denoising problem in interesting settings.
ErA: Error-Aware Deep Unrolling Network for Single Image Defocus Deblurring
Electrical Engineering and Systems Science > Image and Video Processing [Submitted on 4 Jun 2026] Title:ErA: Error-Aware Deep Unrolling Network for Single Image Defocus Deblurring View PDF HTML (experimental)Abstract:We introduce ErA (Error-Aware Deep Unrolling Network), an end-to-end frame work for single-image defocus deblurring.
Tracing a powerful GNSS interference source over Europe
Electrical Engineering and Systems Science > Signal Processing [Submitted on 2 Jun 2026] Title:Chasing Lightning: Detecting, Characterizing, and Identifying a Powerful Space-Based GNSS Interference Source View PDF HTML (experimental)Abstract:This paper analyzes and identifies a space-based Global Navigation Satellite System (GNSS) interference source that has caused scores of powerful transient wide-area interference events over continental Europe, Greenland, and Canada since 2019.
Efficient Multi-Agent Optimization of Optical Power in S+C+L-Band Systems
Electrical Engineering and Systems Science > Systems and Control [Submitted on 4 Jun 2026] Title:Efficient Multi-Agent Optimization of Optical Power in S+C+L-Band Systems View PDF HTML (experimental)Abstract:We propose an AI Agent tailored for link power management in multi-band systems. In S+C+L band span-level study, the agent efficiently solves various optimization objectives.
MPC for nonlinear systems: a comparative review of discretization methods
Electrical Engineering and Systems Science > Systems and Control [Submitted on 4 Jun 2026] Title:MPC for nonlinear systems: a comparative review of discretization methods View PDF HTML (experimental)Abstract:This work provides a comparative review of three different numerical methods generally used to discretize continuous-time non-linear equations appearing in model predictive control problems: direct multiple shooting, direct collocation and successive linearizations. An overview of the...
Unsupervised Learning Based Focal Stack Camera Depth Estimation
Electrical Engineering and Systems Science > Image and Video Processing [Submitted on 14 Mar 2022 (v1), last revised 3 Jun 2026 (this version, v3)] Title:Unsupervised Learning Based Focal Stack Camera Depth Estimation View PDFAbstract:We propose an unsupervised deep learning based method to estimate depth from focal stack camera images. On the NYU-v2 dataset, our method achieves much better depth estimation accuracy compared to single-image based methods.
What's gonna happen to software engineers?
In the back of my mind, I've been thinking a lot about what's going to happen to software developers. In a metaphoric way it feels like an existential question, given that, well, I'm a software developer. The real answer is that nobody really knows.