Optoelectronic devices are advantageous in in-memory light sensing for visual information processing,recognition,and storage in an energy-efficient ***,in-memory light sensors have been proposed to improve the energy,...
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Optoelectronic devices are advantageous in in-memory light sensing for visual information processing,recognition,and storage in an energy-efficient ***,in-memory light sensors have been proposed to improve the energy,area,and time efficiencies of neuromorphic computing *** study is primarily focused on the development of a single sensing-storage-processing node based on a two-terminal solution-processable MoS2 metal-oxide-semiconductor(MOS)charge-trapping memory structure—the basic structure for charge-coupled devices(CCD)—and showing its suitability for in-memory light sensing and artificial visual *** memory window of the device increased from 2.8 V to more than 6V when the device was irradiated with optical lights of different wavelengths during the program ***,the charge retention capability of the device at a high temperature(100 ℃)was enhanced from 36 to 64%when exposed to a light wavelength of 400 *** larger shift in the threshold voltage with an increasing operating voltage confirmed that more charges were trapped at the Al_(2)O_(3)/MoS_(2) interface and in the MoS_(2) layer.A small convolutional neural network was proposed to measure the optical sensing and electricalprogramming abilities of the *** array simulation received optical images transmitted using a blue light wavelength and performed inference computation to process and recognize the images with 91%*** study is a significant step toward the development of optoelectronic MOS memory devices for neuromorphic visual perception,adaptive parallel processing networks for in-memory light sensing,and smart CCD cameras with artificial visual perception capabilities.
This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking pe...
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This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking performance while satisfying the state and input constraints, even when system matrices are not available. We first establish a sufficient condition necessary for the existence of a solution pair to the regulator equation and propose a data-based approach to obtain the feedforward and feedback control gains for state feedback control using linear programming. Furthermore, we design a refined Luenberger observer to accurately estimate the system state, while keeping the estimation error within a predefined set. By combining output regulation theory, we develop an output feedback control strategy. The stability of the closed-loop system is rigorously proved to be asymptotically stable by further leveraging the concept of λ-contractive sets.
Price prediction is one of the examples related to forecasting tasks and is a project based on data science. Price prediction analyzes data and predicts the cost of new products. The goal of this research is to achiev...
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The grid-following inverter's dq admittance model manifests a negative resistance in the low-frequency range due to the phase-locked loop, potentially leading to low-frequency instabilities and limiting the maximu...
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Grid-forming control is considered to be essential in the transition to renewables-dominated power systems. However, grid-forming Type-3 wind turbine generators present unique challenges due to their electromechanical...
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This paper presents a Python-driven graphical user interface (GUI) explicitly crafted for benchmarking the electromagnetic transient (EMT) models of inverter-based resources (IBRs) across Matlab/Simulink and PSCAD/EMT...
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作者:
Anjarlekar, AmeyaEtesami, RasoulSrikant, R.Uiuc
Department of Electrical and Computer Engineering United States Uiuc
Faculty of Electrical and Computer Engineering and Industrial and Systems Engineering United States Uiuc
Faculty of Electrical and Computer Engineering United States
We address a problem involving a buyer seeking to train a logistic regression model by acquiring data from privacy-sensitive sellers. Along with compensating the sellers for their data, the buyer provides differential...
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作者:
Wang, Haozhe ZacWong, Yan TatMonash University
Department of Electrical and Computer Systems Engineering ClaytonVIC3800 Australia Monash University
Department of Electrical and Computer Systems Engineering Department of Physiology ClaytonVIC3800 Australia
Cortical visual prostheses can restore vision by directly stimulating the neurons in the visual cortex. The goal of these prostheses is to elicit sufficient light perception, known as phosphenes, to represent complex ...
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The IEEE 802.1Qbv (80.21Qbv) standard is designed for traffic requiring deterministic and bounded latencies through strict periodic time synchronization, as specified by IEEE 802.1AS standard. However, internal clock ...
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Nanopore sequencing signals can be described as indirect noisy observations that reflect the instantaneous conductance of the nanopore channel as an analyte DNA molecule translocates through the pore in real time, wi...
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