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Compact Model Build Upon Dynamic Weighting Artificial Neural Network Approach for Complementary Field Effect Transistors

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IEEE Transactions on Electron Devices 2024年第1期71卷 246-253页

作者： Butola, Rajat Li, Yiming Kola, Sekhar Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation The Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program The Institute of Communications Engineering the Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan

In this work, a dynamic weighting-artificial neural network (DW-ANN) methodology is presented for quick and automated compact model (CM) generation. It takes advantage of both TCAD simulations for high accuracy and SPICE simulations for cost-effectiveness. This methodology is developed for gate-all-around (GAA) silicon (Si) nanosheet (NS) complementary field effect transistor (CFET), a potential candidate for future CMOS technology due to its innate properties. The critical process variation (PV) sources that severely degrade the CFET performance are estimated using DW-ANN. It reduces the computation cost and predicts the effects of PV sources with less than 1% error. Furthermore, a compact DW-ANN-based Verilog-A model has been developed that captures the dc as well as transient behavior accurately for circuit-level analysis. CFET-based circuits such as inverter, 6T-static random access memory (SRAM), and ring oscillator (RO) are characterized and implemented using DW-ANN-based CM. The overall average error of the model is reported as less than 2%. Therefore, the proposed device and circuit modeling approach provides a feasible solution for the rapid compact modeling of new emerging devices with good convergence and high accuracy. © 1963-2012 IEEE.

关键词： Neural networks

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

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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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Vision-Based Landing Guidance Through Tracking and Orientation Estimation

Vision-Based Landing Guidance Through Tracking and Orientati...

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2025 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2025

作者： Ferreira, João P. K. Pinto, João P. Moura, Júlia Li, Yi Castro, Cristiano L. Angelov, Plamen Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Brazil School of Computing and Communications Lancaster University United Kingdom

ISBN: (纸本)9798331510831

Fixed-wing aerial vehicles are equipped with functional-ities such as ILS (instrument landing system), PAR (precision approach radar) and, DGPS (differential global positioning system), enabling fully automated landings. How-ever, these systems impose significant costs on airport op-erations due to high installation and maintenance requirements. Moreover, since these navigation parameters come from ground or satellite signals, they are vulnerable to in-terference. A more cost-effective and independent alternative for guiding landing is a vision-based system that de-tects the runway and aligns the aircraft, reducing the pi-lot's cognitive load. This paper proposes a novel frame-work that addresses three key challenges in developing au-tonomous vision-based landing systems. Firstly, to over-come the lack of aerial front-view video data, we created high-quality videos simulating landing approaches through the generator code available in the LARD (landing approach runway detection dataset) repository. Secondly, in contrast to former studies focusing on object detection for finding the runway, we chose the state-of-the-art model Lo-RAT to track runways within bounding boxes in each video frame. Thirdly, to align the aircraft with the designated landing runway, we extract runway keypoints from the re-sulting LoRAT frames and estimate the camera relative pose via the Perspective-n-Point algorithm. Our experimental re-sults over a dataset of generated videos and original images from the LARD dataset consistently demonstrate the proposed framework's highly accurate tracking and alignment capabilities. Our approach source code and the Lo-RAT model pre-trained with LARD videos are available at https://***/jpklock2/vision-based-landing-guidance © 2025 IEEE.

关键词： Global positioning system

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A Balloon-Based UAV-Aided Non-Terrestrial Sectorized Network for Post Disaster Cellular Coverage: A Dynamic Environment Perspective 7

A Balloon-Based UAV-Aided Non-Terrestrial Sectorized Network...

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7th International Conference on Advanced Communication Technologies and Networking, CommNet 2024

作者： Dabiri, Mohammad Taghi Hasna, Mazen Althunibat, Saud Qaraqe, Khalid Alouini, Mohamed-Slim Qatar University Department of Electrical Engineering Doha Qatar Al-Hussein Bin Talal University Department of Communications Engineering Jordan Hamad Bin Khalifa University Electrical Engineering Program College of Science and Engineering Qatar King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

ISBN: (纸本)9798350367027

With the advancements in low-earth orbit (LEO) constellations, modern aerial platforms (APs), sector antennas, and device technologies, it is now becoming feasible to provide aerial platform-based cellular network (APCN) as an efficient and easy-To-deploy solution for post-disaster internet recovery. Similar to the terrestrial networks (TNs), sector access antennas have a huge potential for their usage in APs, such as tethered balloons, to provide a wide coverage and high-speed internet connectivity in disaster areas. However, in this paper, we show that many significant challenges remain in their commercial deployments which have received less attention so far. For instance, as the main cause of other challenges, by providing realistic 3D network simulations, we show that sectorized antenna-based APCNs suffer from inherent motions and vibrations of floating AP topologies, which causes moving and dynamic holes in the coverage and thus, confirms that the design of these APCNs is much more complicated than fixed TNs. To this end, by providing an easy-To-read brief review of existing aerospace post-disaster solutions, we show the superiority of APCNs which can bring several key benefits over the existing topologies, and then technically discuss its various challenges and open problems that need to be addressed before they can be deployed at a large scale. © 2024 IEEE.

关键词： Tropics

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Separation of Heart and Lung Sounds by A Deep Network-Based Model 6

Separation of Heart and Lung Sounds by A Deep Network-Based ...

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6th IEEE International Conference on Knowledge Innovation and Invention, ICKII 2023

作者： Tsai, Tung-Sheng Hsu, Chun-Chieh Hsieh, Ching-Lung Liu, Yi-Jui Feng Chia University Program of Electrical and Communications Engineering Taiwan Feng Chia University China Chung Shan Medical University Hospital Taiwan

ISBN: (纸本)9798350323535

Breath and heart sounds are the two main biological sound signals. Heart sounds are produced by the beating of the heart caused by blood flows in the heart valves and blood vessels, while lung sounds are produced by the flow of air in and out of the airways during the breathing cycle. Both signals are recorded from the chest area. However, these two signals are mostly superimposed on each other, so it is of great research interest to separate these heart sound signals (HSS) and lung sound signals (LSS). A "Looking to Listen"model developed by Google, is a joint audiovisual model for isolating a single speech signal from a mix of sounds such as other speakers and background noise. In this study, we evaluated the feasibility of separating HSS and LSS by the audio part of the "Looking to Listen"model. We collected the pure HSS (PHSS) and pure LSS (PLSS) data from the public website (kaggle dataset, CoronaHack Respiratory Sound Dataset). Then, heart and lung sounds (MHLS) were combined HSS and LSS with different weighting power (3:7, 5:5, and 7:3). A total of 8076 MHLSs were generated with 72% of the data in the training set, 10% in the validation set, and 18% in the test set. The cross-correlation coefficient (CC) of pure sound and mixed sound and CC of separated and pure sounds were compared to evaluate the efficacy of extraction HSS or LSS from MHLS. The results showed the mean CC was 0.4, 0.7, and 0.9 for pure HSS and MHLS with 3:7, 5:5, and 7:3, respectively;and the mean CC was 0.79, 0.87, and 0.97 for pure HSS and predicted HSS with 3:7, 5:5, and 7:3, respectively. The mean CC was 0.9, 0.7, and 0.4 for pure LSS and MHLS with 3:7, 5:5, and 7:3, respectively. The mean CC was 0.95, 0.91, and 0.81 for pure LSS and predicted LSS with 3:7, 5:5, and 7:3, respectively. The feasibility of separating HSS and LSS by the audio part of the "Looking to Listen"model was validated. © 2023 IEEE.

关键词： Blood vessels

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A Comprehensive Technique Based on Machine Learning for Device and Circuit Modeling of Gate-All-Around Nanosheet Transistors

IEEE Open Journal of Nanotechnology

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IEEE Open Journal of Nanotechnology 2023年 4卷 181-194页

作者： Butola, Rajat Li, Yiming Kola, Sekhar Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Communications Engineering the Institute of Biomedical Engineering the Department of Electronics and Electrical Engineering the Institute of Pioneer Semiconductor Innovation and the Institute of Artificial Intelligence Innovation Hsinchu300093 Taiwan

Machine learning (ML) is poised to play an important part in advancing the predicting capability in semiconductor device compact modeling domain. One major advantage of ML-based compact modeling is its ability to capture complex relationships and patterns in large datasets. Therefore, in this paper a novel design scheme based on dynamically adaptive neural network (DANN) is proposed to develop fast and accurate compact model (CM). This framework constitutes a powerful yet computationally efficient methodology and exhibits emergent dynamic behaviors. This paper demonstrates that the compact model based on ML can be designed to replicate the performance of conventional compact model for nanodevices. For this work, gate-all-around (GAA) nanosheet (NS) device characteristics are comprehensively analyzed for process variability sources using the proposed model. The device geometry parameters such as channel length, nanosheet width and nanosheet thickness are fed as input features to the DANN model. The adaptive neural network learns dynamically by updating weights of the model in accordance with the input features and achieves accurate neural weight convergence. The proposed model predicted the electrical characteristics of NS devices with less than 1% error rate. The model is also implemented and validated for the simulations of digital circuit designs such as inverter, and logic gates. ©;2023 The Authors.

关键词： Circuit simulation

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Micro-Cantilever Array With Electroplating Tin Bumps for Flip-Chip Bonding Technology

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IEEE Transactions on Components, Packaging and Manufacturing Technology 2023年第12期13卷 2040-2045页

作者： Hu, Zihsong Liou, Chengshiun Tsou, Chingfu Feng Chia University Department of Automatic Control Engineering Taichung40724 Taiwan Institute of Nano Engineering and Microsystems National Tsing Hua University Hsinchu30013 Taiwan Feng Chia University Doctorate Degree of the Ph.D. Program of Electrical and Communications Engineering Taichung40724 Taiwan

A Nickel (Ni) microcantilever beam array with tin (Sn) solder bumps has been designed for flip-chip bonding with high-density electrodes. Micro-electro-mechanical system (MEMS) technology and the micro-electroplating process were used in the fabrication process. Utilizing the out-of-plane deformation of the suspended microcantilever beam, the satisfied heights partially compensate the substrate curvature to ensure a high flip-chip bonding yield, thus, improving package quality in terms of electrical connections. To demonstrate this technique, this study developed a flip-chip carrier for a typical micro-LED array with a beam length of 70~ μm and a bump height of 2~ μm. The measurement results revealed that the displacement of the microcantilever beam was approximately 0.8~ μm when a 500~ μN force was applied on top of the tin bump. When a glass substrate directly mounts to the flip-chip carrier through the tin bump at a heat reflow of 270 °C, most of the tin bumps successfully melt and solidify, which results in good bonding performance. These results revealed that the proposed approach could be applied to the wafer-level packaging process with high-density ball grid array electrodes. © 2011-2012 IEEE.

关键词： Flip chip devices

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Visual Field Examination Technology Based on Semi-transparent Elliptical Mirror 6

Visual Field Examination Technology Based on Semi-transparen...

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6th IEEE Eurasian Conference on Educational Innovation, ECEI 2023

作者： Chang, Chao-Kai Chiang, Chun-Yu Yeh, Feng-Ming Lee, Chi-Hung Tien, Chuen-Lin Chen, Der-Chin Department of Optometry Yuanpei University of Medical Technology Hsinchu Taiwan Ph.D. Program of Electrical and Communications Engineering Feng Chia University Taichung Taiwan Department of Electrical Engineering Feng Chia University Taichung Taiwan

ISBN: (纸本)9798350334289

In this study, the human visual field test technology is established by using an optoelectrical system consisting of a translucent ellipsoid, an area light source, and a landscape scene with an indicator. During the test, the subjects stared at the indicator directly in front of them with one eye and kept their eyeballs still, scanning the light strip with peripheral vision and using the mouse button plus the playback program to record the start and end positions of the scanning light strip in the landscape scene. This method is tested subjectively, and the subject needs to respond during the test. Therefore, before the test, the subject needs to understand the test process and be trained in advance to improve the exam accuracy. In the experiment, fifteen subjects with normal vision and no eye disease were selected. Their visual fields were confirmed normal after a preliminary assessment. The test results showed that the subjects' eyes were within the normal visual field, indicating that this method was feasible. In this research, a digital optical platform for the near visual field is proposed to establish an optoelectric visual field measurement technology. The proposed method is characterized by small size, rapid operation, and easy portability. With the digital LCD and visual imaging technology, both dynamic and static visual fields can be tested. The test data on the eyes' upper, lower, nasal, and temporal sides were consistent with the normal visual field. This shows that this method is feasible and worthy of promotion in the optometry industry. © 2023 IEEE.

关键词： Light sources

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Statistical Device Simulation and Machine Learning of Process Variation Effects of Vertically Stacked Gate-All-Around Si Nanosheet CFETs

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IEEE Transactions on Nanotechnology 2024年 23卷 386-392页

作者： Kola, Sekhar Reddy Li, Yiming Butola, Rajat National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Department of Electronics and Electrical Engineering Institute of Communications Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Biomedical Engineering Institute of Pioneer Semiconductor Innovation Institute of Artificial Intelligence Innovation Hsinchu300093 Taiwan

In this study, we report the process variation effect (PVE) including the work function fluctuation (WKF) on the DC/AC characteristic fluctuation of stacked gate-all-around silicon complementary field-effect transistors (CFETs). The PVE affects characteristic fluctuation significantly;in particular, for the variability of off-state current. Owing to the bottom channel of a fin-type, the P-FET suffers from the worst off-state current fluctuation (more than 200% variation) compared to the N-FET. The device variability induced by the WKF is marginal because of amorphous-type metal grains. As input features to an artificial neural network (ANN) model, low and high work function values, as well as parameters of PVE that have prevalent effects on CEFT transfer characteristics are further considered and modeled. The estimated values of R2-score prove that the ANN model properly grasps information from the dataset successfully;thus, it can be used to model emerging CFETs for circuit simulation. © 2002-2012 IEEE.

关键词： Neural networks

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Adaptive Two-Stage Filter for De-snowing LiDAR Point Clouds 5

Adaptive Two-Stage Filter for De-snowing LiDAR Point Clouds

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5th International Conference on Control, Robotics and Informatics, ICCRI 2022

作者： Le, Minh-Hai Cheng, Ching-Hwa Liu, Don-Gey Nguyen, Thanh-Tuan Feng Chia University Program of Electrical and Communications Engineering Taichung Taiwan Feng Chia University Department of Electronic Engineering Taichung Taiwan

ISBN: (数字)9781665468008

ISBN: (纸本)9781665468008

The Light Detection And Ranging (LiDAR) is integrated into self-driving cars to enhance system reliability. Unfortunately, its effectiveness is severely limited under the extreme weather conditions such as rain, fog, and cloud. This paper proposes an adaptive filter that can remove snow particles (de-snowing) from raw LiDAR point clouds. The proposed method adopts the intensity threshold with a two-stage filter that provides outstanding performance on both accuracy (98%) and processing speed (1.42 frames per second) under extreme environment for the autonomous driving system. © 2022 IEEE.

关键词： Adaptive filters

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