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Large circuit models: opportunities and challenges

Science China(Information Sciences) 2024年第10期67卷 25-66页

作者： Lei CHEN Yiqi CHEN Zhufei CHU Wenji FANG Tsung-Yi HO Ru HUANG Yu HUANG Sadaf KHAN Min LI Xingquan LI Yu LI Yun LIANG Jinwei LIU Yi LIU Yibo LIN Guojie LUO Hongyang PAN Zhengyuan SHI Guangyu SUN Dimitrios TSARAS Runsheng WANG Ziyi WANG Xinming WEI Zhiyao XIE Qiang XU Chenhao XUE Junchi YAN Jun YANG Bei YU Mingxuan YUAN Evangeline F.Y.YOUNG Xuan ZENG Haoyi ZHANG Zuodong ZHANG Yuxiang ZHAO Hui-Ling ZHEN Ziyang ZHENG Binwu ZHU Keren ZHU Sunan ZOU Huawei Noah’s Ark Lab School of Integrated Circuits Peking University Faculty of Electrical Engineering and Computer Science Ningbo University Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Department of Computer Science and Engineering The Chinese University of Hong Kong School of Integrated Circuits Southeast University Huawei HiSilicon Peng Cheng Laboratory School of Computer Science Peking University School of Microelectronics State Key Laboratory of Integrated Chips and System Fudan University School of Artificial Intelligence Shanghai Jiao Tong University

Within the electronic design automation(EDA) domain, artificial intelligence(AI)-driven solutions have emerged as formidable tools, yet they typically augment rather than redefine existing methodologies. These solutions often repurpose deep learning models from other domains, such as vision, text, and graph analytics, applying them to circuit design without tailoring to the unique complexities of electronic circuits. Such an “AI4EDA” approach falls short of achieving a holistic design synthesis and understanding,overlooking the intricate interplay of electrical, logical, and physical facets of circuit data. This study argues for a paradigm shift from AI4EDA towards AI-rooted EDA from the ground up, integrating AI at the core of the design process. Pivotal to this vision is the development of a multimodal circuit representation learning technique, poised to provide a comprehensive understanding by harmonizing and extracting insights from varied data sources, such as functional specifications, register-transfer level(RTL) designs, circuit netlists,and physical layouts. We champion the creation of large circuit models(LCMs) that are inherently multimodal, crafted to decode and express the rich semantics and structures of circuit data, thus fostering more resilient, efficient, and inventive design methodologies. Embracing this AI-rooted philosophy, we foresee a trajectory that transcends the current innovation plateau in EDA, igniting a profound “shift-left” in electronic design methodology. The envisioned advancements herald not just an evolution of existing EDA tools but a revolution, giving rise to novel instruments of design-tools that promise to radically enhance design productivity and inaugurate a new epoch where the optimization of circuit performance, power, and area(PPA) is achieved not incrementally, but through leaps that redefine the benchmarks of electronic systems' capabilities.

关键词： AI-rooted EDA large circuit models (LCMs) multimodal circuit representation learning circuit optimization

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Detecting Pain During Cognitive Tasks via Visibility Graphs of Cortical Signals

Detecting Pain During Cognitive Tasks via Visibility Graphs ...

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IEEE International Symposium on Biomedical Imaging

作者： Ashwini Subramanian Laleh Najafizadeh Department of Electrical and Computer Engineering Integrated System and NeuroImaging Laboratory Rutgers University

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

Detecting pain is critical for developing adaptive systems in clinical and assistive settings, allowing for timely interventions. This work presents an approach to detect the presence of physical pain during the performance of cognitive tasks from cortical signals. Cortical signals from the motor and prefrontal cortices are acquired using functional near in-frared spectroscopy (fNIRS) during two cognitive tasks, per-formed in the absence and presence of physical pain. Visibil-ity graphs (VGs) of these signals are constructed, and graph metrics of averaged clustering coefficient $(C)$ and edge den-sity $(D)$ are extracted. Statistical analysis reveals differences in these metrics for graphs corresponding to tasks performed under no-pain (NP) versus with-pain (WP) conditions, partic-ularly for signals obtained from the motor cortex. The graph metrics were then used as features to a support vector machine (SVM), achieving an accuracy exceeding 80% in distinguishing between tasks performed with and without pain. Our findings suggest that metrics from VGs of cortical sig-nals may serve as potential biomarkers for pain during cog-nitive tasks. This approach could be especially beneficial for non-verbal patients using assistive brain-computer interfaces.

关键词： Measurement Support vector machines Deep learning Pain Statistical analysis Image edge detection Motors Feature extraction Complexity theory Functional near-infrared spectroscopy

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Covert Communications in Active-IOS Aided Uplink NOMA systems With Full-Duplex Receiver

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IEEE Transactions on Vehicular Technology 2025年第5期74卷 8419-8424页

作者： Kang, Xueyu Qi, Nan Lv, Lu Boulogeorgos, Alexandros-Apostolos A. Tsiftsis, Theodoros A. Liu, Hongwu Shandong Jiaotong University School of Information Science and Electrical Engineering Jinan250357 China Nanjing University of Aeronautics and Astronautics Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Nanjing210016 China Xidian University State Key Laboratory of Integrated Services Networks Xi'an710071 China Xidian University School of Telecommunications Engineering Xi'an710071 China University of Western Macedonia Department of Electrical and Computer Engineering Kozani50100 Greece University of Thessaly Department of Informatics and Telecommunications Lamia35100 Greece University of Nottingham Ningbo China Department of Electrical and Electronic Engineering Ningbo315100 China

In this paper, an active intelligent omni-surface (A-IOS) is deployed to aid uplink transmissions in a non-orthogonal multiple access (NOMA) system. In order to shelter the covert signal embedded in the superposition transmissions, a multi-antenna full-duplex (FD) receiver is utilized at the base-station to recover signal in addition to jamming the warden. With the aim of maximizing the covert rate, the FD transmit and receive beamforming, A-IOS refraction and reflection beamforming, NOMA transmit power, and FD jamming power are jointly optimized. To tackle the non-convex covert rate maximization problem subject to the highly coupled system parameters, an alternating optimization algorithm is designed to iteratively solve the decoupled sub-problems of optimizing the system parameters. The optimal solutions for the sub-problems of the NOMA transmit power and FD jamming power optimizations are derived in closed-form. To tackle the rank-one constrained non-convex fractional programming of the A-IOS beamforming and FD beamforming, a penalized Dinkelbach transformation approach is proposed to resort to the optimal solutions via semidefinite programming. Numerical results clarify that the deployment of the A-IOS significantly improves the covert rate compared with the passive-IOS aided uplink NOMA system. It is also found that the proposed scheme provides better covert communication performance with the optimized NOMA transmit power and FD jamming power compared with the benchmark schemes. © 1967-2012 IEEE.

关键词： Jamming

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Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 18-36页

作者： Ding Wang Ning Gao Derong Liu Jinna Li Frank L.Lewis IEEE the Faculty of Information Technology Beijing Key Laboratory of Computational Intelligence and Intelligent SystemBeijing Laboratory of Smart Environmental Protectionand Beijing Institute of Artificial IntelligenceBeijing University of TechnologyBeijing 100124China the School of System Design and Intelligent Manufacturing Southern University of Science and TechnologyShenzhen 518055China the Department of Electrical and Computer Engineering University of Illinois at ChicagoChicago IL 60607 USA the School of Information and Control Engineering Liaoning Petrochemical UniversityFushun 113001China the UTA Research Institute the University of Texas at ArlingtonArlington TX 76118 USA

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, ***, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation ***, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

关键词： Adaptive dynamic programming(ADP) advanced control complex environment data-driven control event-triggered design intelligent control neural networks nonlinear systems optimal control reinforcement learning(RL)

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Comprehensive Overview of Multi-agent systems for Controlling Smart Grids

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CSEE Journal of Power and Energy systems 2022年第1期8卷 115-131页

作者： Om Prakash Mahela Mahdi Khosravy Neeraj Gupta Baseem Khan Hassan Haes Alhelou Rajendra Mahla Nilesh Patel Pierluigi Siano Power System Planning Division Rajasthan Rajya Vidyut Prasaran Nigam Ltd.Jaipur-302005India Media Integrated Communication Laboratory Graduate School of EngineeringOsaka UniversityOsakaJapan Computer Science and Engineering Department Oakland UniversityRochesterUSA Department of Electrical and Computer Engineering Hawassa UniversityHawassa 1530Ethiopia Faculty of Mechanical and Electrical Engineering Tishreen UniversityLattakiaSyria Department of Electrical Engineering National Institute of Technology Kurukshetra Department of Management&Innovation Systems University of Salerno84084 SalernoItaly

Agents are intelligent entities that act flexibly and autonomously and make wise decisions based on their intelligence and experience.A multi-agent system(MAS)contains multiple,intelligent,and interconnected collaborating agents for solving a problem beyond the ability of a single agent.A smart grid(SG)combines advanced intelligent systems,control techniques,and sensing methods with an existing utility power *** controlling smart grids,various control systems with different architectures have already been ***-based control of power system operations has been shown to overcome the limitations of time required for analysis,relaying,and protection;transmission switching;communication protocols;and management of plant *** systems provide an alternative for fast and accurate power network *** paper provides a comprehensive overview of MASs used for the control of smart *** paper provides a wide-spectrum view of the status of smart grids,MAS-based control techniques and their implementation for the control of smart *** of MASs in the control of various aspects of smart grids-including the management of energy,marketing energy,pricing,scheduling energy,reliability,network security,fault handling capability,communication between agents,SG-electrical vehicles,SG-building energy systems,and soft grids—have been critically *** than a hundred publications on the topic of MAS-based control of smart grids have been critically examined,classified,and arranged for fast reference.

关键词： Coordinated control multi-agent systems renewable energy sources smart energy infrastructure smart grid

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High-Performance Placement Engine for Modern Large-Scale FPGAs with Heterogeneity and Clock Constraints

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IEEE Transactions on computer-Aided design of integrated Circuits and systems 2024年第3期43卷 956-969页

作者： Zhu, Ziran Mei, Yangjie Deng, Kangkang He, Huan Chen, Jianli Yang, Jun Chang, Yao-Wen Southeast University National ASIC System Engineering Research Center School of Integrated Circuits Nanjing210096 China Peking University Beijing International Center for Mathematical Research Beijing100871 China Hangzhou Huawei Enterprises Telecommunication Technologies Company Ltd. Central Hardware Planning & Architecture Design Department Hangzhou310000 China Fudan University State Key Laboratory of ASIC and System Shanghai200433 China National Taiwan University Graduate Institute of Electronics Engineering The Department of Electrical Engineering Taipei10617 Taiwan

As field-programmable gate array (FPGA) architectures continue to evolve and become more complex, the heterogeneity and clock constraints imposed by modern FPGAs have posed significant challenges to FPGA placement. This article proposes a high-performance placement engine for modern large-scale FPGAs with heterogeneity and clock constraints. To improve efficiency and scalability, we develop a clustering method considering both internal/external connectivity and the balance of block types to build the hierarchy. In each hierarchy level, we propose a hybrid penalty and augmented Lagrangian method (HPALM) to convert the FPGA global placement with heterogeneity and clock constraints into a series of unconstrained optimization subproblems, then use the Adam method to solve each subproblem. In particular, we prove that the HPALM is globally convergent for global placement. Besides, a matching-based IP block legalization is developed to legalize the DSPs and RAMs, and a multistage packing is presented to cluster LUTs and FFs into HCLBs. Finally, we propose a history-based legalization to legalize CLBs in an FPGA, and a simulated-annealing-based detailed placement is presented to reduce the wirelength while maintaining legality. Compared with the state-of-the-art works, experimental results based on the ISPD 2017 contest benchmarks show that the proposed algorithm can achieve the shortest routed wirelength in a reasonable runtime. © 1982-2012 IEEE.

关键词： Table lookup

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A 200V Monolithic GaN Dynamic Floating Voltage Level Shifter with Nanosecond Propagation Delays and Noise-Immune Slewing Control

A 200V Monolithic GaN Dynamic Floating Voltage Level Shifter...

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Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Fei Zhou D. Brian Ma Department of Electrical and Computer Engineering Integrated Power Electronics System Laboratory The University of Texas at Dallas Richardson TX USA

Monolithic GaN power IC has been regarded as the ultimate solution to unlock the full potential of the wide bandgap GaN technology for next-generation high-speed, high-efficiency and high-density power circuits. However, with scarce power device options, the current development of monolithic GaN power ICs faces severe design challenges. A critical example can be found in the design of one of the most important circuit modules – the voltage level shifter, which is the enabler to drive any kind of high-side power switch in a power circuit. To overcome this challenge, this paper proposes a new circuit structure and a novel operation concept of a dynamic floating voltage level shifter to reduce propagation delays, improve dynamic slew rates and attain superb dv⁄dt noise immunity for both speed and reliability improvements. Implemented on a 200V, 180nm, n-type only, GaN-on-SOI process, the proposed voltage level shifter only occupies a die area of 0.12mm 2 and achieves 2.81ns rising and 3.44ns falling propagation delays at room temperature with a slew rate of 100V/ ns.

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A ΔIIN Self-Canceled SEPIC Power Converter for EMI CISPR 25 Compliance

A ΔIIN Self-Canceled SEPIC Power Converter for EMI CISPR 25...

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Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Zhenda Fu Lixiong Du Jin Woong Kwak Fei Zhou D. Brian Ma Department of Electrical and Computer Engineering Integrated Power Electronics System Laboratory The University of Texas at Dallas Richardson TX USA

In an effort to comply with stringent electromagnetic interference (EMI) standards for automotive electronics applications, this paper introduces a new SEPIC converter topology with significantly reduced di/dt switching dynamics for conducted EMI suppression. The converter employs a unique T circuit network, consisting of a coupled inductor and an auxiliary LC branch, to self-cancel its input current ripple ΔI IN , thus minimizing associated di/dt. By doing so, the converter incurs no significant power density and efficiency penalties. Meanwhile, the converter requires no active control circuitry to ensure accurate ΔI IN cancelation, simplifying the design complexity. To demonstrate the converter topology and design ideas, a converter prototype is designed, which accommodates a wide input supply voltage range of 4.5V to 40V and delivers an output of 12V, with seamless buck-boost conversion operation. Operating at 400kHz, it delivers a maximum power of 42W and achieves a peak efficiency of 86.8%. For the step-up conversion with 5V V IN and 500mA load, the ΔI IN self-canceled SEPIC topology achieves 9.6dB peak EMI reduction at the fundamental frequency. For the step-down conversion with 1.5A load, it reduces the peak EMI by 20.4dB and 13.9dB at V IN of 24V and 40V, respectively, satisfying the CISPR25 Class 2 Standards.

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A Conduction-Loss-Conscious 4-Level Power Converter with Tri-Path Synchronous Rectification for High Step-Down DC-DC Conversion

A Conduction-Loss-Conscious 4-Level Power Converter with Tri...

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Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Jin Woong Kwak D. Brian Ma Department of Electrical and Computer Engineering Integrated Power Electronics System Laboratory The University of Texas at Dallas Richardson TX USA

Multi-level power converters today are highly desirable for high step-down DC-DC conversions but face a serious challenge due to the inherent limitations of topology and operation, which severely impacts efficiency. To combat this challenge, this paper proposes a new operation strategy - tri-path synchronous rectification (TSR) to reduce conduction loss in each discharge phase significantly, which is regarded as a dominant factor to efficiency. The TSR strategy is non-intrusive and can be virtually applied to any multi-level converters without interrupting the original converter operation. To demonstrate the design ideas, a 4-level TSR converter prototype is designed and tested. It down-converts a 48V power source to an output voltage programmable from 1V to 2V with a maximum load of 25A and a peak efficiency of 90.8%.

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3D-Printed Stainless Steel Electrodes for Advancing Mems Microbial Fuel Cells Toward Sustainable on-chip Energy 38

3D-Printed Stainless Steel Electrodes for Advancing Mems Mic...

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38th IEEE International Conference on Micro Electro Mechanical systems, MEMS 2025

作者： Elhadad, Anwar Li, Guangfa Yang, Jiaqi Liu, Dehao Choi, Seokheun State University of New York at Binghamton Integrated Computational Materials Design Lab Department of Mechanical Engineering BinghamtonNY United States State University of New York at Binghamton Bioelectronics & Microsystems Laboratory Department of Electrical & Computer Engineering BinghamtonNY United States State University of New York at Binghamton Center for Research in Advanced Sensing Technologies and Environmental Sustainability BinghamtonNY United States

ISBN: (纸本)9798331508890

This study introduces a stainless steel microbial anode fabricated via advanced laser powder bed fusion, marking a transformative step in microbial fuel cell (MFC) technology. By leveraging this cutting-edge metal 3D printing approach, we achieve a 3D microporous structure with superior electrical conductivity, outstanding corrosion resistance in aquatic environments, robust mechanical strength, and adaptability for surface modification - essential attributes for sustainable, high-performance MFCs. The assembled MFC demonstrates unparalleled power output, along with exceptional durability and stability over multiple cycles, outperforming existing MFCs based on alternative 3D-printed substrates. This advancement not only solidifies the role of MFCs as a sustainable energy solution for powering on-chip electronics but also opens new avenues for scalable, cost-effective bioelectronic systems that align with the demands of next-generation technology. © 2025 IEEE.

关键词： Corrosion resistance

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