Results 31 to 40 of about 17,761 (290)
Active Learning in Physics: From 101, to Progress, and Perspective
Advanced Quantum Technologies, EarlyView., 2023 In this review, the concept of active learning is introduced to the physicists at the level of beginner without requirement on background in machine learning. It includes most of the latest applications of active learning in branches of physics, covering but not being limited to quantum information, high energy physics, and condensed matter physics. It
Yongcheng Ding +3 more
wiley +1 more source
Fuzzy Hilbert Transform of Fuzzy Functions
MathematicsThis paper studies the properties of the Fourier transform of the fuzzy function, and extends the classical Poisson integral formula on the half plane to the fuzzy case, obtaining the composition of the fuzzy set generated by a point in the complex field
Zhibo Yan
doaj +1 more source
Energies, 2020 Penetration level of renewable energy (RE) in the utility grid is continuously increasing to minimize the environmental concerns, risk of energy security, and depletion of fossil fuels.
Govind Sahay Yogee +6 more
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On the Maximal Directional Hilbert Transform [PDF]
Analysis Mathematica, 2019 29 pages, 8 figures.
A. Marinelli +2 more
openaire +3 more sources
A General Approach to Dropout in Quantum Neural Networks
Advanced Quantum Technologies, EarlyView., 2023 Randomly dropping artificial neurons and all their connections in the training phase reduces overfitting issues in classical neural networks, thus improving performances on previously unseen data. The authors introduce different dropout strategies applied to quantum neural networks, learning models based on parametrized quantum circuits.
Francesco Scala +3 more
wiley +1 more source
Decomposition of Multicomponent Micro-Doppler Signals Based on HHT-AMD
Applied Sciences, 2018 Micro-Doppler signals analysis has been emerging as an important topic in target identification, and relative research has been focusing on features extraction and separation of the radar signals.
Wenchao Li, Gangyao Kuang, Boli Xiong
doaj +1 more source
Advanced Photonics Research, EarlyView.Coherent anti‐stokes Raman spectroscopy (CARS) enables high‐resolution vibrational imaging, yet non‐resonant background (NRB) distorts spectral fidelity. This review highlights NRB removal methods—from experimental strategies and numerical algorithms to emerging deep learning techniques.
Rajendhar Junjuri, Thomas Bocklitz
wiley +1 more source
Benefits of Open Quantum Systems for Quantum Machine Learning
Advanced Quantum Technologies, EarlyView., 2023 Quantum machine learning (QML), poised to transform data processing, faces challenges from environmental noise and dissipation. While traditional efforts seek to combat these hindrances, this perspective proposes harnessing them for potential advantages. Surprisingly, under certain conditions, noise and dissipation can benefit QML.
María Laura Olivera‐Atencio +2 more
wiley +1 more source
IEEE Access, 2021 This paper presents an algorithm for numerical Hilbert transform of functions represented by cubic and exponential splines, which is suitable for causal interpolation of data spanning several frequency decades. It does not suffer from excessive number of
Dusan N. Grujic
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Network Desynchronization with Sine Waves: from Synchrony to Asynchrony by Periodic Stimulation
Advanced Science, EarlyView.Exogenous alternating current fields are explored and interact with cerebral cortex slow waves in vitro and in silico. Varying frequency and amplitude of sine waves result in distinct network dynamics, from phase‐locking and entrainment to desynchronization. These responses occupy specific regions within the parameter space.
Joana Covelo +4 more
wiley +1 more source