Results 61 to 70 of about 53,557 (225)

Synchronization of Analog Neuron Circuits With Digital Memristive Synapses: An Hybrid Approach

Advanced Electronic Materials, EarlyView.
An hybrid circuit mimicking neural units coupled using memristive synapses is introduced. The analog neurons provide flexibility and robustness, and the digital memristive coupling guarantees the full reconfigurability of the interconnection. The onset of a synchronized spiking behavior in two circuits mimicking the Izhikevich neuron is discussed from ...
Lamberto Carnazza, Francesco Maria Esposito, Carlo Famoso, Arturo Buscarino   +3 more
wiley   +1 more source

Uncertainty Propagation and Global Sensitivity Analysis of a Surface Acoustic Wave Gas Sensor Using Finite Elements and Sparse Polynomial Chaos Expansions

Vibration, 2023
The aim of this work is to perform an uncertainty propagation and global sensitivity analysis of a surface acoustic wave (SAW) gas sensor using finite elements and sparse polynomial chaos.
Mohamed Hamdaoui
doaj   +1 more source

Performance of Modal Signaling vs. medium dielectric variability [PDF]

, 2012
This paper addresses the feasibility of the so-called Modal Signaling (MS) transmission scheme from a stochastic viewpoint. MS has been proposed for crosstalk mitigation over interconnects and is based on the encoding of signals onto fundamental ...
Canavero, Flavio, Manfredi, Paolo, Stievano, Igor Simone   +2 more
core   +1 more source

CFD modeling and sensitivity‐guided design of silicon filament CVD reactors

AIChE Journal, EarlyView.
Abstract Filament‐based chemical vapor deposition (CVD) for silicon (Si) coatings is often treated as an adaptation of planar deposition. But this overlooks fundamental shifts in transport phenomena and reaction kinetics. In filament CVD, the filament acts as a substrate, heat source, and flow disruptor simultaneously. In this work, we ask: What really
G. P. Gakis, G. Loachamín‐Suntaxi, I. G. Aviziotis, E. D. Koronaki, P. P. Filippatos, G. Chatzigiannakis, S. P. A. Bordas, D. Davazoglou, A. G. Boudouvis   +8 more
wiley   +1 more source

Small Sample-Based Fatigue Reliability Analysis Using Non-Intrusive Polynomial Chaos

IEEE Access, 2020
Based on small sample of fatigue test data, a new method to obtain p-S-N curve for fatigue reliability analysis using non-intrusive polynomial chaos (NIPC) is proposed to lower test cost.
Xiaoran Liu, Qin Sun
doaj   +1 more source

Generalized decoupled polynomial chaos for nonlinear circuits with many random parameters [PDF]

, 2015
This letter proposes a general and effective decoupled technique for the stochastic simulation of nonlinear circuits via polynomial chaos. According to the standard framework, stochastic circuit waveforms are still expressed as expansions of orthonormal ...
Canavero, Flavio, De Zutter, Daniël, Manfredi, Paolo, Vande Ginste, Dries   +3 more
core   +2 more sources

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

Advanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows, G. Zhang, S. Anand, Z. Chen, J. Lin, A. Desai, S. Martiniani, F. Caravelli   +7 more
wiley   +1 more source

Best Practices in Developing a Workflow for Uncertainty Quantification for Modeling the Biodegradation of Mg‐Based Implants

Advanced Science
Computational models of electrochemical biodegradation of magnesium (Mg)‐based implants are uncertain. To quantify the model uncertainty, iterative evaluations are needed.
Tamadur AlBaraghtheh, Regine Willumeit‐Römer, Berit Zeller‐Plumhoff   +2 more
doaj   +1 more source

Polynomial chaos expansions for damped oscillators

, 2015
Uncertainty quantification is the state-of-the-art framework dealing with uncertainties arising in all kind of real-life problems. One of the framework’s functions is to propagate uncertainties from the stochastic input factors to the output quantities of interest, hence the name uncertainty propagation.
Mai, Chu V., Sudret, Bruno
openaire   +2 more sources

Machine Learning‐Driven Variability Analysis of Process Parameters for Semiconductor Manufacturing

Advanced Intelligent Systems, EarlyView.
This research presents a machine learning approach that integrates nonlinear variation decomposition (NLVD) with statistical techniques to quantify the contribution of individual unit processes to performance and variance of figure of merit (FoM) at the LOT level.
Sinyeong Kang, Hyeok Yun, Kyeongrae Cho, Seungjoon Eom, Soomin Kim, Seongsoo Jeong, Rockhyun Baek   +6 more
wiley   +1 more source