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2023 China Automation Congress, CAC 2023

作者： Li, Jiazhuo Chen, Luefeng Li, Min Wu, Min Pedrycz, Witold Hirota, Kaoru The School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Wuhan430074 China The Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada The Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland The Department of Computer Engineering Istinye University Sariyer Istanbul34396 Turkey The Tokyo Institute of Technology Tokyo226-8502 Japan

ISBN: (纸本)9798350303759

With the rapid advances in computer vision, human action recognition has gradually received attention, but the current methods still exhibit some problems in indoor environments. The human skeleton, as the framework of human motion, contains high-quality actional feature information, and the skeleton-based action recognition method effectively avoid the interference of interior background noise and has advantages in indoor action recognition. The outstanding effect of graph convolutional networks on graph structure data processing has led to its rapid development and wide application in skeleton-based action recognition. Second-order skeletal information also contains a large number of actional features but is not effectively utilized. The artificial predefined topology of the human skeleton map has limitations, and cannot reflect the interaction between limbs. To solve the above problems, this article designs an adaptive weighted multi-stream graph convolutional network (AM-GCN) based on skeletal information, using an attention mechanism to enhance the network's ability to extract actional features, and an adaptive layer to make the construction graph more flexible, incorporating second-order skeletal features through a dual-stream architecture. In this article, the NTU-RGB+D dataset has been used for the experiments, the results show that the method in this article has good results. © 2023 IEEE.

关键词： Convolution

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Ge2Sb2Se4Te Phase Change Material Monolithic Platform for Integrated Photonics

Ge2Sb2Se4Te Phase Change Material Monolithic Platform for In...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Acharjee, Niloy Sun, Hongyi Ghosh, Siddhartha Ríos Ocampo, Carlos A. Institute for Research in Electronics & Applied Physics University of Maryland College ParkMD20742 United States Department of Electrical & Computer Engineering University of Maryland College ParkMD20742 United States Department of Materials Science & Engineering University of Maryland College ParkMD20742 United States Space Systems - Northrop Grumman 1 Space Park Blvd Redondo BeachCA90278 United States

ISBN: (纸本)9781957171395

We demonstrate a monolithic Ge2Sb2Se4Te platform for tunable photonic integrated circuits. We fabricated and measured various on-chip components, including waveguides with preliminary 55.7±3.65 dB/cm propagation loss. Refractive index tuning is demonstrated via post-fabrication localized crystallization. © Optica Publishing Group 2024 © 2024 The Author(s)

关键词： System-on-chip

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An Iterative Method for a Frequency Domain PID Controller Synthesis

An Iterative Method for a Frequency Domain PID Controller Sy...

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SICE Annual Conference

作者： Kenjiro Minamikawa Yasushi Kami Eitaku Nobuyama Atsushi Hosokawa Department of Mechanical and Electronic System Engineering Advanced Course of National Institute of Technology Akashi College Hyogo Japan Department of Electrical Systems Engineering Hiroshima Institute of Technology Hiroshima Japan Department of Intelligent and Control Systems Kyushu Institute of Technology Fukuoka Japan Department of Electrical and Computer Engineering National Institute of Technology Akashi College Hyogo Japan

This study is concerned with a control system design method with frequency response data named a finite number of frequency responses(an FNFR) model. In this paper a numerical descent direction is introduced and an iterative method for solving control problems formulated with the FNFR model is proposed with the descent direction. One feature of our approach is to update controller variables so that they approach to a feasible region of considering control problems from the outside. The efficiency of our method is shown by numerical examples.

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Decentralized State Estimation and Opacity Verification Based on Partially Ordered Observation Sequences

arXiv

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arXiv 2025年

作者： Sun, Dajiang Hadjicostis, Christoforos N. Li, Zhiwu School of Electro-Mechanical Engineering Xidian University Xi’an710071 China Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Institute of Systems Engineering Macau University of Science and Technology Taipa999078 China

In this paper, we investigate state estimation and opacity verification problems within a decentralized observation architecture. Specifically, we consider a discrete event system whose behavior is recorded by a set of observation sites. These sites transmit the partially ordered sequences of observations that they record to a coordinator whenever a synchronization occurs. To properly analyze the system behavior from the coordinator’s viewpoint, we first introduce the notion of a Complete Synchronizing Sequence structure (CSS structure), which concisely captures the state evolution of each system state upon different information provided by the observation sites. Based on the CSS structure, we then construct corresponding current-state and initial-state estimators for offline state estimation at the coordinator. When used to verify state-isolation properties under this decentralized architecture, the use of CSS structure demonstrates a significant reduction in complexity compared with existing approaches in the literature. In particular, we discuss how to verify initial-state opacity at the coordinator, as well as a novel opacity notion, namely current-state-at-synchronization opacity. Copyright © 2025, The Authors. All rights reserved.

关键词： Decentralized systems

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Adaptive Beamforming Based on Interference-Plus-Noise Covariance Matrix Reconstruction for Speech Separation

Adaptive Beamforming Based on Interference-Plus-Noise Covari...

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Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)

作者： Yongxiong Xiao Shiqiang Zhu Te Li Minhong Wan Wei Song Jason Gu Qiang Fu Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Lab Hangzhou China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou China Department of Electrical and Computer Engineering Dalhousie University Halifax NS Canada

Estimating the interference-plus-noise covariance matrix (INCM) is critical for the robustness of the minimum variance distortionless response (MVDR) beamformer. Existing INCM reconstruction methods are computationally intensive and not suitable for real-time speech separation. We propose a singular value decomposition (SVD) based INCM reconstruction method for speech separation. The spatial covariance matrix (SCM) for each source is obtained by rank-1 approximation using the nominal steering vector (SV) or the pre-measured relative transfer function (RTF). The INCM used to separate each source is reconstructed as the sum of the covariance matrices of interference and spherical isotropic noise. The proposed method is evaluated using the mixed signal received by a circular array with six microphones placed in a simulated reverberation chamber. The results show that the proposed method has comparable sound quality performance to the reference method, but requires much less computation.

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Online Learning in Blockchain-based Energy Trading systems 24

Online Learning in Blockchain-based Energy Trading Systems

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2024 International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, MobiHoc 2024

作者： Liu, Yunshu Cheung, Man Hon Huang, Jianwei Pillar of Engineering Systems and Design Singapore University of Technology and Design Singapore Singapore Department of Computer Science City University of Hong Kong Hong Kong School of Science and Engineering Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen Key Laboratory of Crowd Intelligence Empowered Low-Carbon Energy Network CSIJRI Joint Research Centre on Smart Energy Storage The Chinese University of HongKong Guangdong Shenzhen518172 China

ISBN: (纸本)9798400705212

In this paper, we consider a blockchain-based energy trading (BBET) system with the proof-of-stake (PoS) protocol. The system designer aims to minimize system cost by considering the prosumers’ strategic token allocation between blockchain staking and energy purchase for their applications. This is challenging as the system designer does not know prosumers’ private information of impatience levels towards different applications. To this end, we propose an online learning mechanism (OLM), which includes incentive mechanisms to guide both prosumers’ private information reporting and staking decisions in two phases. In the exploration phase, we design a randomized staking reward to encourage prosumers’ truthful reporting of their private information for the learning of impatience level distributions. Based on the threshold structure of the prosumers’ equilibrium staking strategies, in the exploitation phase, we propose a learning-error-based reward to minimize the system cost considering the finite-sample bias. By characterizing the optimal exploration duration, we prove that OLM achieves an asymptotic zero-regret against the complete information benchmark, with the regret bounded by O(3√lnT/T) when operating for T time slots. We implement the corresponding smart contract in Ethereum to demonstrate the feasibility of our approach. Experiment results show that our mechanism reduces regret by an average of 74% compared to the state-of-art mechanism. © 2024 Copyright held by the owner/author(s).

关键词： Blockchain

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Aircraft Classification Using Flight Phase Identification

Aircraft Classification Using Flight Phase Identification

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IEEE National Conference on Aerospace and Electronics (NAECON)

作者： Sarah Bolton Richard Dill Michael R. Grimaila Douglas D. Hodson Department of Electrical and Computer Engineering Air Force Institute of Technology OH USA Department of Systems Engineering and Management Air Force Institute of Technology Wright-Patterson AFB OH USA

Flight data collected from an Automatic Dependent Surveillance-Broadcast (ADS-B) can be used to make inferences about aircraft characteristics. This work uses all flight phases to identify an aircraft's Wake Turbulence Category (WTC), aircraft description and type designator as described in the International Civil Aviation Organization (ICAO) Document 8643.

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KKL Observer Synthesis for Nonlinear systems via Physics-Informed Learning

arXiv

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arXiv 2025年

作者： Niazi, M.B. Umar Cao, John Barreau, Matthieu Johansson, Karl Henrik Division of Decision and Control Systems Digital Futures KTH Royal Institute of Technology StockholmSE-100 44 Sweden Laboratory for Information and Decision Systems Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical Engineering Stanford University StanfordCA94305 United States

This paper proposes a novel learning approach for designing Kazantzis-Kravaris/Luenberger (KKL) observers for autonomous nonlinear systems. The design of a KKL observer involves finding an injective map that transforms the system state into a higher-dimensional observer state, whose dynamics is linear and stable. The observer’s state is then mapped back to the original system coordinates via the inverse map to obtain the state estimate. However, finding this transformation and its inverse is quite challenging. We propose to sequentially approximate these maps by neural networks that are trained using physics-informed learning. We generate synthetic data for training by numerically solving the system and observer dynamics. Theoretical guarantees for the robustness of state estimation against approximation error and system uncertainties are provided. Additionally, a systematic method for optimizing observer performance through parameter selection is presented. The effectiveness of the proposed approach is demonstrated through numerical simulations on benchmark examples and its application to sensor fault detection and isolation in a network of Kuramoto oscillators using learned KKL observers. © 2025, CC BY.

关键词： State estimation

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Live Demonstration: A fully embedded adaptive real-time hand gesture classifier leveraging HD-sEMG and deep learning

Live Demonstration: A fully embedded adaptive real-time hand...

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IEEE Biomedical Circuits and systems (BIOCAS)

作者： Xavier Isabel Thomas Labbé Félix Chamberland Étienne Buteau Evan Campbell Ulysse Côté-Allard Simon Tam Paul Fortier Alexandre Campeau-Lecours Mounir Boukadoum Erik Scheme Benoit Gosselin Electrical Engineering and Computer Engineering Department Laval University Institute of Biomedical Engineering University of New-Brunswick Department off Technology Systems University of Oslo Mechanical Engineering Department Laval University Computer Science Department University of Quebec at Montreal

In a fully immersive virtual reality setting, visitors will actively participate in our demonstration, engaging in an interactive videogame utilizing our cutting-edge HD-sEMG Bracelet. Prior to this, they will undergo state-of-the-art training to personalize their machine learning gesture recognition model. The gameplay will be broadcast on a computer monitor, allowing onlookers to observe while the demonstrator explains the core concept of our work. By wearing the bracelet, the player gains control over their limb in a game inspired by Simon Says. Throughout the demonstration, visitors will gain firsthand experience and knowledge about the forthcoming advantages of HD-sEMG for control applications, such as prosthesis control. They will also discover how the EMaGer HD-sEMG Bracelet capitalizes on its uniform and high electrode density to enhance the reliability of hand gesture recognition models utilized in myoelectric prosthesis control.

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Plate Shape Prediction Based on Data-Driven in Roll Quenching Process

Plate Shape Prediction Based on Data-Driven in Roll Quenchin...

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2023 China Automation Congress, CAC 2023

作者： Hu, Liu Chen, Luefeng Hu, Jie Wu, Min Pedrycz, Witold Hirota, Kaoru School of Automation Ministry of Education China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6R 2G7 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University The Department of Computer Engineering Istanbul Sariyer34396 Turkey Tokyo Institute of Technology Tokyo Yokohama226-8502 Japan

ISBN: (纸本)9798350303759

In the process of steel plate production, predicting the plate shape is of great significance for producing high-quality and consistently stable plate shapes. This paper presents a model that predicts both the defect types and flatness of the plate, providing theoretical support for setting process parameters in roller quenching production. First, the parameters of the quenching process are analyzed to identify their characteristics. Then, the K-Means clustering algorithm and correlation analysis are employed to process the quenching process parameters. A gradient boosting decision tree (GBDT) model is used to predict the defect types and flatness of the steel plates. Finally, industrial production data is utilized for experimental validation. The obtained experimental results verify the reliability of the proposed method. © 2023 IEEE.

关键词： Decision trees

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