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A Physical-Based Artificial Neural Networks Compact Modeling Framework for Emerging FETs

IEEE Transactions on Electron Devices 2024年第1期71卷 223-230页

作者： Yang, Ya-Shu Li, Yiming Kola, Sekhar Reddy Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory The Institute of Communications Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Institute of Communications Engineering Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan

We report a compact modeling framework based on the Grove-Frohman (GF) model and artificial neural networks (ANNs) for emerging gate-all-around (GAA) MOSFETs. The framework consists of two ANNs;the first ANN constructed with the drain current model not only can capture the main trend of device I - V characteristics but also can predict its variation even when the amount of training data for the ANN is insufficient or outside the range of applied biases. The second one is then designed to improve the model accuracy by further minimizing the errors between the target and the model outputs. We implement the proposed framework to accurately model emerging GAA nanosheet (NS) MOSFETs and complementary FETs (CFETs) without suffering from divergent issues in circuit simulation. In addition, nonphysical behaviors, such as nonzero current at zero bias, do not occur in the modeling framework. Compared to recently reported machine-learning (ML) models, our approach can achieve a similar level of model accuracy with merely 20% amount of the training data. © 1963-2012 IEEE.

关键词： Neural networks

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Effect of Yttrium Treatment on Germanium-Oxide-Based Interfacial Layer of Ge P-Channel Metal–Oxide–Semiconductor Field-Effect Transistor Fabricated Through In Situ Plasma-Enhanced Atomic Layer Deposition

引用

IEEE Transactions on Electron Devices 2024年第3期71卷 1-6页

作者： Li, Hui-Hsuan Lin, Kuan-Yu Tsai, Yi-He Lin, Yu-Hsien Chien, Chao-Hsin Institute of Electronics National Yang Ming Chiao Tung University Hsinchu Taiwan Graduate Program for Nanotechnology Department of Materials Science and Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Electronic Engineering National United University Miaoli Taiwan

This study investigated the effect of yttrium (Y) treatment on a germanium (Ge)-oxide-based interfacial layer (IL) through in situ plasma-enhanced atomic layer deposition (PEALD). Time-of-flight secondary-ion mass spectrometry revealed that the surface reaction and deposition could be successfully performed with a Y precursor, and X-ray photoelectron spectroscopy (XPS) revealed that Y treatment on an IL can suppress GeO

$_{\text{x}}$

volatilization. A metal–oxide–semiconductor capacitor gate-stack with a Y-GeO

$_{\text{x}}$

IL has a low leakage current density (2.1

$\times$

$^{-\text{5}}$

A/cm

$^{\text{2}}$

) and a low interface trap density (approximately 5.5

$\times$

$^{\text{11}}$

$^{-\text{1}}$

$^{-\text{2}}$

) under optimized temperatures. Moreover, the Ge P-channel metal–oxide–semiconductor field-effect transistor (P-MOSFET) containing a gate-stack with a Y-treated Ge-oxide-based IL exhibited a high I

$_{\biosc{on}}$

$_{\biosc{off}}$

ratio and low OFF-state current. Therefore, applying the proposed Y treatment on the IL of a Ge P-MOSFET can help achieve a subnanometer equivalent oxide thickness (EOT) and an

关键词： Ge-oxide-based germanium germanium oxide (GeOx) in situ interfacial layer (IL) plasma-enhanced atomic layer deposition (PEALD) Y-GeOx yttrium

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A Developed PLL Control Technique for Distorted and Unbalanced Grid Voltages with a Three-Level NPC Converter-Based Off-Board Battery Charger

A Developed PLL Control Technique for Distorted and Unbalanc...

引用

2022 International electrical engineering Congress, iEECON 2022

作者： Thanakam, Thidarat Kumsuwan, Yuttana Chiang Mai University Graduate Program in Electrical Engineering Department of Electrical Engineering Faculty of Engineering Chiang Mai Thailand Chiang Mai University Faculty of Engineering Department of Electrical Engineering Chiang Mai Thailand

ISBN: (纸本)9781665402064

As electric vehicle technologies advance, the number of off-board battery charger stations grows. Because they can provide a high-power level that is suitable for fast charging. The main factor of high-power transferring is power converters that should serve the grid power quality, including the reactive power, the power factor, and the harmonic distortion. In this paper, the development of the control algorithm for the three-phase three-level neutral point clamped converter-based off-board battery charger to support the utility grid when the three-phase grid voltage distortion or unbalance occurs is presented. By applying the standard phase-locked loop controller into the conventional control algorithm, it is possible to obtain more sinusoidal and balanced grid currents along with distorted or unbalanced grid voltages to conserve the grid power quality. The system operations, along with the comparison of the conventional control algorithm and the proposed algorithm, are provided in the simulation results. © 2022 IEEE.

关键词： Charging (batteries)

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Into 3D-Reconstructed Apparel over Virtual Try-On with Virtual Reality

Into 3D-Reconstructed Apparel over Virtual Try-On with Virtu...

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2023 International Conference on Consumer electronics - Taiwan, ICCE-Taiwan 2023

作者： Doungtap, Surasachai Petchhan, Jirayu Phanichraksaphong, Varinya Wang, Jenq-Haur International Graduate Program of Electrical Engineering and Computer Science Taiwan National Taiwan University of Science & Technology Dept. of Electrical Engineering Taiwan National Taipei University of Technology Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9798350324174

Virtualization technologies are still growing bigger and faster. Despite the greatness of its advancement, the costume industry is still very accessible when it comes to real trials. Off-the-shelf stuff are inadequate details for the desired individual to assess its in-depth utility for each garment trying on for a second, including custom stuff are much harder to try out right away. To this end, 2D image-based 3D reconstruction inclusive of touchable-virtualized space is accessible easier to stuff details for mans' decision making in purchasing. We establish the overall end-to-end pipeline from reconstruction until visualization for one instance to be triable on its stuff for a moment. As an expectation, our proposed approach can bring objects into the experimental area and use them immediately without any obstacle. © 2023 IEEE.

关键词： Virtual reality

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A High-Performance Grid-Tied Three-Level T-Type Converter for Off-Board Battery Chargers under AC-Side Voltage Distortions and Unbalances 19

A High-Performance Grid-Tied Three-Level T-Type Converter fo...

引用

19th International Conference on electrical engineering/electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2022

ISBN: (纸本)9781665485845

The conversions are a key factor in the battery charging of electric vehicles. The off-board battery chargers, which are composed of converters and controller units, are needed to fast charge by transferring high-power. The converters should serve applications even with unusual grid systems where non-sinusoidal grid currents occur. This paper describes a high-performance, three-level T-type converter for off-board battery chargers. It can operate under conditions of grid voltage distortions and grid voltage unbalances. The proposed control algorithm provides the three-phase sinusoidal currents to prevent their effect on the grid system and the equipment, which is an improvement from the conventional control algorithm. The constant current and constant voltage modes are applied for charging applications. Moreover, the power factor correction can be obtained. The simulation results are provided to investigate the performance of the off-board battery charger based on the three-level T-type converter. © 2022 IEEE.

关键词： Charging (batteries)

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Analysis of Maximum Power Transfer Limit for Linear Operation of Dual-Active-Bridge Converters 14

Analysis of Maximum Power Transfer Limit for Linear Operatio...

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14th Annual IEEE Applied Power electronics Conference and Exposition, APEC 2025

作者： Sarda, Radhika Rodriguez, Ezequiel Ramos Liang, Gaowen Farivar, Glen G. Pou, Josep Sriram, Vaisambhayana B. Tripathi, Anshuman Nanyang Technological University Energy Research Institute at Ntu Interdisciplinary Graduate Programme Singapore Nanyang Technological University Energy Research Institute at Ntu Singapore University of Melbourne Department of Electrical and Electronic Engineering Melbourne Australia City University of Hong Kong Department of Electrical Engineering Hong Kong

ISBN: (纸本)9798331516116

In power electronics applications where the dual-active-bridge (DAB) converter topology serves as an isolation stage between high-impedance input and output ports, significant voltage fluctuations can arise during transient conditions. These variations restrict the DAB converter's maximum power transfer capacity and narrow its linear operating region, a limitation further exacerbated when low-capacitance capacitors are used at the DAB converter terminals. This paper introduces a comprehensive control design framework tailored to maximize the DAB converter's power transfer capacity, accommodating a range of input and output capacitor sizes. Additionally, we examine multiple control strategies that directly influence voltage variations at the DAB converter terminals, demonstrating their critical role when trying to maximize the DAB converter's power capacity. © 2025 IEEE.

关键词： Electric converters

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SNeRV: Spectra-preserving Neural Representation for Video

arXiv

引用

arXiv 2025年

作者： Kim, Jina Lee, Jihoo Kang, Je-Won Department of Electronic and Electrical Engineering Graduate Program in Smart Factory Ewha Womans University Seoul Korea Republic of

Neural representation for video (NeRV), which employs a neural network to parameterize video signals, introduces a novel methodology in video representations. However, existing NeRV-based methods have difficulty in capturing fine spatial details and motion patterns due to spectral bias, in which a neural network learns high-frequency (HF) components at a slower rate than low-frequency (LF) components. In this paper, we propose spectra-preserving NeRV (SNeRV) as a novel approach to enhance implicit video representations by efficiently handling various frequency components. SNeRV uses 2D discrete wavelet transform (DWT) to decompose video into LF and HF features, preserving spatial structures and directly addressing the spectral bias issue. To balance the compactness, we encode only the LF components, while HF components that include fine textures are generated by a decoder. Specialized modules, including a multi-resolution fusion unit (MFU) and a high-frequency restorer (HFR), are integrated into a backbone to facilitate the representation. Furthermore, we extend SNeRV to effectively capture temporal correlations between adjacent video frames, by casting the extension as additional frequency decomposition to a temporal domain. This approach allows us to embed spatio-temporal LF features into the network, using temporally extended up-sampling blocks (TUBs). Experimental results demonstrate that SNeRV outperforms existing NeRV models in capturing fine details and achieves enhanced reconstruction, making it a promising approach in the field of implicit video representations. The codes are available at https://***/qwertja/SNeRV. Copyright © 2025, The Authors. All rights reserved.

关键词： Discrete wavelet transforms

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A Neural Computing-Based Access Control Protocol for AI-Driven Intelligent Flying Vehicles in Industry 5.0-Assisted Consumer electronics

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IEEE Transactions on Consumer electronics 2024年第1期70卷 3573-3581页

作者： Mahmood, Khalid Tariq, Tayyaba Sangaiah, Arun Kumar Ghaffar, Zahid Saleem, Muhammad Asad Shamshad, Salman National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan National Yunlin University of Science and Technology Department of Computer Science and Information Engineering Douliu64002 Taiwan National Yunlin University of Science and Technology International Graduate School of AI Douliu64002 Taiwan Lebanese American University Department of Electrical and Computer Engineering Byblos1102 2801 Lebanon University of Electronic Science and Technology of China School of Computer Science and Engineering Sichuan Chengdu611731 China The University of Lahore Department of Software Engineering Lahore54590 Pakistan

The continuous revolution in Artificial Intelligence (AI) has played a significant role in the development of key consumer applications, including Industry 5.0, autonomous decision-making, fault diagnosis, etc. In practice, autonomous and intelligent robots and flying vehicles (i.e., drones) are also becoming the integral part of Industry 5.0. These vehicles are attaining significant importance nowadays because of their applications in consumer electronics. However, there may be numerous privacy issues in such an infrastructure. Nevertheless, neural computing-driven security solutions have played a significant role in overcoming the security and privacy issues of AI-driven intelligent flying vehicles. Motivated by these facts, this article presents a neural computing-based access control protocol for AI-driven flying vehicles to prevent all possible security threats. A detailed security evaluation of the devised protocol is done formally using the extensively recognized Real-Or-Random (ROR) oracle model. Similarly, the informal security analysis ensures the resistance of our scheme against various potential attacks under the assumptions of CK and DY adversarial models. Moreover, detailed performance scrutiny of the devised protocol with various existing schemes shows the robustness and supremacy of our scheme in terms of computation, communication overhead, and security attributes. © 1975-2011 IEEE.

关键词： Authentication

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Quantum-resistant Cryptography in FPGA 7

Quantum-resistant Cryptography in FPGA

引用

7th Workshop on Communication Networks and Power Systems, WCNPS 2022

作者： Policarpo, Renata C. Nery, Alexandre S. Albuquerque, Robson De O. University of Brasília Professional Post-Graduate Program in Electrical Engineering Department of Electrical Engineering Brasilia70910-900 Brazil

ISBN: (数字)9781665474566

ISBN: (纸本)9781665474566

The use of cryptography techniques to guarantee confidentiality, authenticity and integrity of sensitive data has become mandatory. Besides, advancements in quantum computers are gradually posing a threat to public key encryption technology. Without proper security measures, fraudsters may easily gain access to one's personal and sensitive data. The result of the third round of NIST's Post-Quantum Cryptography (PQC) process for standardization of public-key cryptography systems brought CRYSTALS-Kyber as the first mechanism selected for key encapsulation. The aim of this study is to provide the specification of a reconfigurable CRYSTAL-Kyber accelerator using High-Level Synthesis (HLS) technology. Our architecture requires about 2200 LUTs, 3001 FFs and 28 DSP on a low-cost Zynq FPGA (XC7Z020-1 CLG400C). The total time spent by the accelerator in a key exchange simulation is approximately 0.84 ms, operating at 100 MHz, and the estimated power consumption in this process is 1.695W. © 2022 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Spectral Learning of Shared Dynamics Between Generalized-Linear Processes 38

Spectral Learning of Shared Dynamics Between Generalized-Lin...

引用

38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Oganesian, Lucine L. Sani, Omid G. Shanechi, Maryam M. Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los AngelesCA United States Ming Hsieh Department of Electrical and Computer Engineering Thomas Lord Department of Computer Science Alfred E. Mann Department of Biomedical Engineering Neuroscience Graduate Program University of Southern California Los AngelesCA United States

Generalized-linear dynamical models (GLDMs) remain a widely-used framework within neuroscience for modeling time-series data, such as neural spiking activity or categorical decision outcomes. Whereas the standard usage of GLDMs is to model a single data source, certain applications require jointly modeling two generalized-linear time-series sources while also dissociating their shared and private dynamics. Most existing GLDM variants and their associated learning algorithms do not support this capability. Here we address this challenge by developing a multi-step analytical subspace identification algorithm for learning a GLDM that explicitly models shared vs. private dynamics within two generalized-linear time-series. In simulations, we demonstrate our algorithm's ability to dissociate and model the dynamics within two time-series sources while being agnostic to their respective observation distributions. In neural data, we consider two specific applications of our algorithm for modeling discrete population spiking activity with respect to a secondary time-series. In both synthetic and real data, GLDMs learned with our algorithm more accurately decoded one time-series from the other using lower-dimensional latent states, as compared to models identified using existing GLDM learning algorithms. © 2024 Neural information processing systems foundation. All rights reserved.

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