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IEEE International Conference on computer-Aided Design

作者： Shengxi Shou Che-Kai Liu Sanggeon Yun Zishen Wan Kai Ni Mohsen Imani X. Sharon Hu Jianyi Yang Cheng Zhuo Xunzhao Yin College of Information Science and Electronic Engineering Zhejiang University China Department of Information and Computer Science University of California Irvine USA School of Electrical and Computer Engineering Georgia Institute of Technology USA Department of Electrical and Microelectronic Engineering Rochester Institute of Technology USA Department of Computer Science and Engineering University of Notre Dame USA School of Micro-Nano Electronics. Zhejiang University China Key Laboratory of Collaborative Sensing and Autonomous Unmaned Systems of Zhejiang Province China

Artificial intelligence has made remarkable advancements in recent years, leading to the development of algorithms and models capable of handling ever-increasing amounts of data. The computational demands of these algorithms necessitate circuit and architecture designs that go beyond the von-Neumann paradigm. Content addressable memories (CAMs), which implement parallel associative search functionality within memory blocks to overcome the memory wall bottleneck, have proven to be effective for data-intensive tasks. While current CAM designs have achieved higher storage density and energy efficiency than their CMOS-based counterparts by leveraging emerging non-volatile memories (NVM), most of these implementations are limited to binary storage cells. In this work, we propose SEE-MCAM, scalable and compact multi-bit CAM (MCAM) designs that utilize the three-terminal ferroelectric FET (FeFET) as the proxy. By exploiting the multi-level-cell characteristics of FeFETs, our proposed SEE-MCAM designs enable multi-bit associative search functions and achieve better energy efficiency and performance than existing FeFET-based CAM designs. We validated the functionality of our proposed designs by achieving 3 bits per cell CAM functionality, resulting in 3x improvement in storage density. The area per bit of the proposed SEE-MCAM cell is 8% of the conventional CMOS CAM. We thoroughly investigated the scalability and robustness of the proposed design. Evaluation results suggest that the proposed 2FeFET-1 T SEE-MCAM achieves 9.8× more energy efficiency and 1.6× less search latency compared to the CMOS CAM, respectively. When compared to existing MCAM designs, the proposed SEE-MCAM can achieve 8.7× and 4.9× more energy efficiency than ReRAM-based and FeFET-based MCAMs, respectively. Benchmarking results show that our approach provides up to 3 orders of magnitude improvement in speedup and energy efficiency over a GPU implementation in accelerating a novel quantized hyperdimensiona

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A Continuous Off-Policy Reinforcement Learning Scheme for Optimal Motion Planning in Simply-Connected Workspaces

A Continuous Off-Policy Reinforcement Learning Scheme for Op...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Panagiotis Rousseas Charalampos P. Bechlioulis Kostas J. Kyriakopoulos School of Mechanical Engineering Control Systems Laboratory National Technical University of Athens Greece Department of Electrical and Computer Engineering University of Patras Center of AI & Robotics (CAIR) New York University Abu Dhabi

In this work, an Integral Reinforcement Learning (RL) framework is employed to provide provably safe, convergent and almost globally optimal policies in a novel Off-Policy Iterative method for simply-connected workspaces. This restriction stems from the impossibility of strictly global navigation in multiply connected manifolds, and is necessary for formulating continuous solutions. The current method generalizes and improves upon previous results, where parametrized controllers hindered the method in scope and results. Through enhancing the traditional reactive paradigm with RL, the proposed scheme is demonstrated to outperform both previous reactive methods as well as an RRT* method in path length, cost function values and execution times, indicating almost global optimality.

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A 0.9–1.4-GHz Q-Enhanced CMOS Tunable Bandpass Filter With Constant Fractional Bandwidth and Two Transmission Zeros

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IEEE Microwave and Wireless Technology Letters 2023年第6期33卷 667-670页

作者： Kun Li Xiang Li Shuangyang Wu Pei-Ling Chi Tao Yang School of Electronic Science and Engineering University of Electronic Science and Technology of China Chengdu China Research Center of Advanced RF Chips and Systems Nanhu Laboratory Jiaxing China Department of Electrical and Computer Engineering National Chiao Tung University Hsinchu Taiwan

A tunable differential $Q$ -enhanced bandpass filter covering 0.9–1.4 GHz with constant fractional bandwidth (FBW) is proposed using 40-nm CMOS technology in this letter. The proposed filter is constructed by two resonators which consist of ON-chip integrated inductors and varactors. The inductors of the two resonators are placed close to each other to form the mainline magnetic coupling of the filter. Besides the mainline coupling, the source port and load port are connected directly by capacitors, forming the source-to-load coupling. With the proposed structure, two transmission zeros (TZs) can be obtained, which can greatly increase the stopband rejection. Meanwhile, nMOS cross-coupled pairs are used as the $Q$ -enhanced cells to reduce the insertion loss (IL) and further improve the filter selectivity. A filter prototype based on 40-nm CMOS process is fabricated to validate the proposed structure. The center frequency (CF) of the proposed filter can be tuned from 0.9 to 1.4 GHz while keeping the FBW constant at 8%.

关键词： Resonator filters Band-pass filters Microwave filters Filtering theory Couplings Equivalent circuits Magnetic separation

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Resilience-oriented Operation of Power Distribution Networks with Line Hardening and Comprehensive Reconfiguration Measures

Resilience-oriented Operation of Power Distribution Networks...

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IEEE International Conference on Smart Grid Communications (SmartGridComm)

作者： Zhengmao Li Zhao Shi Guangchun Ruan Yuzhang Lin Jin Zhao School of Electrical Engineering Aalto University Espoo Finland School of Electrical and Electronic Engineering Nanyang Technological University Singapore Laboratory for Information & Decision Systems Massachusetts Institute of Technology Boston The USA Department of Electrical and Computer Engineering New York University New York the USA Department of Electronic and Electrical Engineering Trinity College Dublin Dublin Ireland

With the frequent occurrence of extreme events like natural disasters and man-made attacks, the resilience concept is attracting worldwide research attention. Thus, this paper proposes a resilient operation model for the power distribution network (PDN) to recover load and limit economic loss to the greatest possible extent. First, the line hardening measure is applied to strengthen the PDN to avoid the serious breakdown of distribution lines. In addition, a comprehensive single commodity flow-based reconfiguration approach is used which not only sets the buses connecting generation sources but also those at the end of broken lines as the slack buses. Then, the radiality of PDNs can still be guaranteed after reconfiguration. The resilience-oriented operation problem can be originally formulated as a nonlinear programming one while efficient linearization methods are applied to reduce computational burdens. Hence, the operation problem is reformulated as a mixed-integer linear programming one which will enjoy favorable solution performances. Finally, case studies on an IEEE 33 PDN including comparison cases with traditional benchmarks are done to show the effectiveness of our method.

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State Derivative Normalization for Continuous-Time Deep Neural Networks

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IFAC-PapersOnLine 2024年第15期58卷 253-258页

作者： Jonas Weigand Gerben I. Beintema Jonas Ulmen Daniel Görges Roland Tóth Maarten Schoukens Martin Ruskowski Chair of Machine Tools and Control Systems RPTU Kaiserslautern and the German Research Center for Artificial Intelligence Kaiserslautern Germany Control Systems (CS) Group at the Department of Electrical Engineering Eindhoven University of Technology Netherlands. R. Tóth is also affiliated to the Systems and Control Laboratory at the Institute for Computer Science and Control Budapest Hungary Institute for Electromobility RPTU Kaiserslautern Germany

The importance of proper data normalization for deep neural networks is well known. However, in continuous-time state-space model estimation, it has been observed that improper normalization of either the hidden state or hidden state derivative of the model estimate, or even of the time interval can lead to numerical and optimization challenges with deep learning based methods. This results in a reduced model quality. In this contribution, we show that these three normalization tasks are inherently coupled. Due to the existence of this coupling, we propose a solution to all three normalization challenges by introducing a normalization constant at the state derivative level. We show that the appropriate choice of the normalization constant is related to the dynamics of the to-be-identified system and we derive multiple methods of obtaining an effective normalization constant. We compare and discuss all the normalization strategies on a benchmark problem based on experimental data from a cascaded tanks system and compare our results with other methods of the identification literature.

关键词： System Identification Continuous-Time Neural Ordinary Differential Equations Nonlinear State-Space

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Low-Power Envelope Detector for WSN Wake-up Receiver Applications

Low-Power Envelope Detector for WSN Wake-up Receiver Applica...

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IEEE International Conference on Design & Test of Integrated Micro & Nano-systems (DTS)

作者： Mariem Bouraoui Amel Neifar Imen Barraj Mohamed Masmoudi Electrical Engineering Department Systems Integration and Emerging Energies Laboratory National Engineers School of Sfax University of Sfax Sfax Tunisia National Engineers School of Gabes University of Gabes Tunisia Department of Computer Engineering College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Al-Kharj Saudi Arabia

This paper highlights the importance of the wake-up receiver in applications using WSN while offering a brief description of this element. In this work, the design of a low-power envelope detector for wake-up receiver applications is presented. By using RF-TSMC CMOS 0.18μm, the proposed envelope circuit is designed for 52 GHz frequency. The forward body biasing method is employed to decrease the circuit energy consumption. The proposed circuit can achieve 152MHz cut-off frequency over the operating frequency range and has power dissipation of 87.5μW under 1V.

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PLC and Human Machine Interface based PV Condition Monitoring Structure Comprising an Innovative Fault Detection Scheme

PLC and Human Machine Interface based PV Condition Monitorin...

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International Conference on Energy Transition in the Mediterranean Area (SyNERGY MED)

作者： Amir Nedaei Aref Eskandari Nima Pourshahbaz Sherko Salehpour Parviz Parvin Andreas Livera George Makrides Mohammadreza Aghaei Department of Electrical Engineering Amirkabir University of Technology (AUT) Tehran Iran Department of Electrical Engineering Iran University of Science and Technology (IUST) Tehran Iran Department of Physics and Energy Engineering Amirkabir University of Technology (AUT) Tehran Iran Department of Electrical and Computer Engineering PV Technology Laboratory University of Cyprus (UCY) PHAENTON Centre of Excellence for Intelligent Efficient and Sustainable Energy Solutions Nicosia Cyprus Department of Electrical and Computer Engineering PV Technology Laboratory University of Cyprus (UCY) PHAETHON Centre of Excellence for Intelligent Efficient and Sustainable Energy Solutions Nicosia Cyprus Department of Ocean Operations and Civil Engineering Norwegian University of Science and Technology (NTNU) Ålesund Norway Department of Sustainable Systems Engineering (INATECH) University of Freiburg Freiburg Germany

ISBN: (数字)9798350375923

ISBN: (纸本)9798350375930

Photovoltaic (PV) systems operate outdoors and are inevitably exposed to various environmental stresses. These stresses may result in several faults and failures which can affect the PV proper performance in terms of reducing the output power and even in some catastrophic cases may end in fire hazards. Therefore, PV systems need to be constantly and carefully monitored to maintain their appropriate performance. In this paper, a condition monitoring (CM) scheme is proposed based on the Programmable Logic Controller (PLC). The scheme is capable to detect line-to-line (LL) and line-to-ground (LG) faults on the DC-side of the PV array and also enables the system to track the maximum power point (MPP) and provides the operator with the real-time PV information via Human-Machine Interface (HMI).

关键词： Condition monitoring Photovoltaic systems Human-machine systems Programmable logic devices Programmable logic arrays Real-time systems Hazards Logic Stress Monitoring

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An Intelligent Condition Monitoring Scheme For Photovoltaic systems using Programmable Logic Controller

An Intelligent Condition Monitoring Scheme For Photovoltaic ...

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International Conference on Energy Transition in the Mediterranean Area (SyNERGY MED)

ISBN: (数字)9798350375923

ISBN: (纸本)9798350375930

Environmental and other stresses are constantly affecting photovoltaic (PV) components which can end in various faults. The anomalous condition can reduce the PV output power or even result in a calamitous fire hazard. Hence, PV systems must be monitored constantly in order to ensure their proper performance. This paper proposes an intelligent PV condition monitoring scheme based on Programmable Logic Controller (PLC). This scheme monitors the PV performance and detects different faults and failures on the DC-side of the array. It also takes advantage of Human-Machine Interface (HMI) which provides the operators with useful real-time data from the array.

关键词： Condition monitoring Photovoltaic systems Human-machine systems Programmable logic devices Real-time systems Arrays Logic Monitoring Stress Logic arrays

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Variational Bayesian Learning Based Localization and Channel Reconstruction in RIS-aided systems

arXiv

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arXiv 2024年

作者： Li, Yunfei Luo, Yiting Wu, Xianda Shi, Zheng Ma, Shaodan Yang, Guanghua The Department of Electrical Engineering Anhui Polytechnic University Wuhu City China The School of Electronics and Information Engineering South China Normal University Foshan528000 China The School of Intelligent Systems Science and Engineering Jinan University Zhuhai519070 China The State Key Laboratory of Internet of Things for Smart City the Department of Electrical and Computer Engineering University of Macau Taipa China

The emerging immersive and autonomous services have posed stringent requirements on both communications and localization. By considering the great potential of reconfigurable intelligent surface (RIS), this paper focuses on the joint channel estimation and localization for RIS-aided wireless systems. As opposed to existing works that treat channel estimation and localization independently, this paper exploits the intrinsic coupling and nonlinear relationships between the channel parameters and user location for enhancement of both localization and channel reconstruction. By noticing the non-convex, nonlinear objective function and the sparser angle pattern, a variational Bayesian learning-based framework is developed to jointly estimate the channel parameters and user location through leveraging an effective approximation of the posterior distribution. The proposed framework is capable of unifying near-field and far-field scenarios owing to exploitation of sparsity of the angular domain. Since the joint channel and location estimation problem has a closed-form solution in each iteration, our proposed iterative algorithm performs better than the conventional particle swarm optimization (PSO) and maximum likelihood (ML) based ones in terms of computational complexity. Simulations demonstrate that the proposed algorithm almost reaches the Bayesian Cramer-Rao bound (BCRB) and achieves a superior estimation accuracy by comparing to the PSO and the ML algorithms. Copyright © 2024, The Authors. All rights reserved.

关键词： Maximum likelihood estimation

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An integrated microfluidic platform for nucleic acid testing

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Microsystems & Nanoengineering 2024年第3期10卷 181-194页

作者： Antao Sun Petra Vopařilová Xiaocheng Liu Bingqian Kou TomášŘezníček TomášLednický Sheng Ni JiříKudr Ondřej Zítka Zdenka Fohlerová Petr Pajer Haoqing Zhang Pavel Neužil Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace School of Mechanical EngineeringNorthwestern Polytechnical University127 West Youyi RoadXi’anShaanxi 710072P.R.China Department of Chemistry and Biochemistry Mendel University in BrnoZemědělská161300 BrnoCzech Republic ITD Tech s.r.o Osvoboditelů100573581 BohumínCzech Republic Central European Institute of Technology Brno University of TechnologyPurkyňova 123Brno 61200Czech Republic Department of Electronic and Computer Engineering The Hong Kong University of Science and TechnologyClear Water BayKowloonHong Kong SARChina Department of Microelectronics Faculty of Electrical Engineering and CommunicationBrno University of TechnologyTechnická3058/10Brno 61600Czech Republic Military Health Institute U Vojenskénemocnice 120016200 Praha 6Czech Republic The Key Laboratory of Biomedical Information Engineering of Ministry of Education School of Life Science and TechnologyXi’an Jiaotong UniversityXi’anShaanxi 710049P.R.China Bioinspired Engineering and Biomechanics Center(BEBC) Xi’an Jiaotong UniversityXi’an 710049P.R.China

This study presents a rapid and versatile low-cost sample-to-answer system for SARS-CoV-2 *** system integrates the extraction and purification of nucleic acids,followed by amplification via either reverse transcriptionquantitative polymerase chain reaction(RT–qPCR)or reverse transcription loop-mediated isothermal amplification(RT–LAMP).By meeting diverse diagnostic and reagent needs,the platform yields testing results that closely align with those of commercial RT-LAMP and RT‒qPCR *** advantages of our system include its speed and *** assay is completed within 28 min,including sample loading(5 min),ribonucleic acid(RNA)extraction(3 min),and RT-LAMP(20 min).The cost of each assay is≈$9.5,and this pricing is competitive against that of Food and Drug Administration(FDA)-approved commercial *** some RNA loss during on-chip extraction is observed,the platform maintains a potential limit of detection lower than 297 *** makes the system particularly useful in environments where centralized laboratories are either unavailable or inconveniently *** key feature is the platform’s versatility,allowing users to choose between RT‒qPCR or RT‒LAMP tests based on specific requirements.

关键词： testing maintain versatile

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