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Differential Linear Matrix Inequalities in Optimal and Robust Sampled-Data Filtering

IFAC-PapersOnLine 2023年第2期56卷 9806-9811页

作者： Henrique W.R. Pereira Gabriela W. Gabriel André M. de Oliveira José C. Geromel Electronic Engineering Division ITA São José dos Campos SP Brazil Institute of Science and Technology UNIFESP São José dos Campos SP Brazil School of Electrical and Computer Engineering UNICAMP Campinas SP Brazil

This paper tackles the design of a robust filter for sampled-data linear time-invariant systems subject to parameter uncertainties. After the optimal solution is obtained, the two major classes of parameter uncertainty are considered, namely, convex bounded and norm bounded. For each of them, the filter associated to the minimum H2 guaranteed performance is determined. The design conditions are expressed through differential linear matrix inequalities (DLMIs), a mathematical device well adapted to cope with sampled-data systems because it naturally avoids matrix exponential and similar mappings. In this framework, the optimal nominal filter is determined, and it is shown that it exhibits a time-invariant observer-based structure. Illustrative examples are presented and discussed in order to put in clear evidence the theoretical results.

关键词： Sampled-data filtering robust estimation convex optimization observer design

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Zeroth-Order and Vortex Bessel Beams from Single-Mode Fibers with 3D Printed Photonic Structures

Zeroth-Order and Vortex Bessel Beams from Single-Mode Fibers...

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Conference on Lasers and Electro-Optics Europe (CLEO EUROPE)

作者： Innem V.A.K Reddy Andrea Bertoncini Carlo Liberale Biological and Environmental Science and Engineering Division King Abdullah University of Science and Technology Saudi Arabia Department of Electrical Engineering University at Buffalo NY USA Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology Saudi Arabia

ISBN: (纸本)9798350345995

Diffraction-free propagation and self-healing characteristics [1] of Bessel beams have generated significant interest in the scientific community. Zeroth-order Bessel beams (ZOBBs) have maximum intensity at the center and found many applications, including bio-imaging material processing, optical trapping, bio-imaging, and quantum communication. On the other hand, higher-order (vortex) Bessel beams (HOBBs) present a helical wavefront, so they have a node due to a phase singularity and carry orbital angular momentum (OAM). Over the past years, Bessel beams have been generated by using different approaches - which could be different for ZOBBs and HOBBs - namely by Fourier transforming a narrow circular beam with a lens, by using axicons or with holographic beam shaping techniques.

关键词： Beam shaping Fourier transforms Materials processing Optical trapping Optical vortices Single mode fibers

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WiFo: Wireless Foundation Model for Channel Prediction

arXiv

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arXiv 2024年

作者： Liu, Boxun Gao, Shijian Liu, Xuanyu Cheng, Xiang Yang, Liuqing State Key Laboratory of Photonics and Communications School of Electronics Peking University Beijing100871 China Guangzhou511400 China Department of Electronic and Computer Engineering Department of Civil and Environmental Engineering The Hong Kong University of Science and Technology Hong Kong

Channel prediction permits to acquire channel state information (CSI) without signaling overhead. However, almost all existing channel prediction methods necessitate the deployment of a dedicated model to accommodate a specific configuration. Leveraging the powerful modeling and multi-task learning capabilities of foundation models, we propose the first space-time-frequency (STF) wireless foundation model (WiFo) to address time-frequency channel prediction tasks in a unified manner. Specifically, WiFo is initially pre-trained over massive and extensive diverse CSI datasets. Then, the model will be instantly used for channel prediction under various CSI configurations without any fine-tuning. We propose a masked autoencoder (MAE)based network structure for WiFo to handle heterogeneous STF CSI data, and design several mask reconstruction tasks for self-supervised pre-training to capture the inherent 3D variations of CSI. To fully unleash its predictive power, we build a large-scale heterogeneous simulated CSI dataset consisting of 160K CSI samples for pre-training. Simulations validate its superior unified learning performance across multiple datasets and demonstrate its state-of-the-art (SOTA) zero-shot generalization performance via comparisons with other full-shot baselines. Copyright © 2024, The Authors. All rights reserved.

关键词： Zero-shot learning

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GCN-Enhanced Multi-Agent MAC Protocol for Vehicular Communications 22

GCN-Enhanced Multi-Agent MAC Protocol for Vehicular Communic...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Li, Mengfei Wang, Wei Feng, Shijie Fu, Tiange Wang, Yan Zhang, Hui State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China Sichuan Jiuzhou Electronic Group Co. Ltd. Mianyang621000 China Department of Civil and Environmental Engineering The Hong Kong Polytechnic University Hong Kong School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China

ISBN: (纸本)9798331527471

In the vehicular ad-hoc network (VANET) environment, the constant changes in traffic systems due to the real-time mobility of vehicles pose a challenge in developing communication strategies that can swiftly adapt to dynamic topological variations. Traditional protocols such as CSMA/CD offer dynamic access to shared media, but their efficiency is compromised by CSMA/CA’s collision avoidance strategy, which reduces channel use due to its backoff algorithm. This paper introduces a novel Graph Convolutional Network-based Multi-Agent Reinforcement Learning MAC protocol (GMMAC) for vehicular networks. Unlike the Neuro-DCF protocol, GMMAC incorporates local vehicular data directly, enabling more context-aware learning. Compared to other GNN-based MARL approaches like GraphComm, GMMAC better handles real-time changes and interactions among vehicles. Experimental results show that GMMAC significantly improves successful transmission numbers and reduces collisions, outperforming traditional CSMA/CA methods and other MARL approaches without GCN integration. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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Brain Tumor Classification using Vision Transformer with Selective Cross-Attention Mechanism and Feature Calibration

arXiv

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arXiv 2024年

作者： Khaniki, Mohammad Ali Labbaf Mirzaeibonehkhater, Marzieh Manthouri, Mohammad Hasani, Elham Faculty of Electrical Engineering K.N. Toosi University of Technology Tehran Iran Department of Electrical and Computer Engineering Indiana University Purdue University United States Faculty of Electrical and Electronic Engineering Shahed university Tehran Iran Department of Chemical and Environmental Engineering University of Cincinnati CincinnatiOH45221 United States

Brain tumor classification is a challenging task in medical image analysis, with significant implications for patient diagnosis and treatment. The objective of this paper is to propose a novel approach to brain tumor classification using a Vision Transformer (ViT) with a novel cross-attention mechanism. Our approach leverages the strengths of transformers in modeling long-range dependencies and multi-scale feature fusion. We introduce two new mechanisms to improve the performance of the cross-attention fusion module: Feature Calibration Mechanism (FCM) and Selective Cross-Attention (SCA). FCM calibrates the features from different branches to make them more compatible, while SCA selectively attends to the most informative features. Our experimental results demonstrate that the proposed approach outperforms other state-of-the-art methods, including Convolutional Neural Networks (CNN), ViT, and Cross-attention ViT, achieving an accuracy of 98.93% and an F1-score of 98.83%. Furthermore, the addition of Stochastic Depth mechanism improves the accuracy to 99.24% and the F1-score to 99.23%. The proposed FCM and SCA mechanisms can be easily integrated into other ViT architectures, making them a promising direction for future research in medical image analysis. Copyright © 2024, The Authors. All rights reserved.

关键词： Convolutional neural networks

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A GTFS data acquisition and processing framework and its application to train delay prediction

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International Journal of Transportation Science and Technology 2023年第1期12卷 201-216页

作者： Jianqing Wu Bo Du Zengyang Gong Qiang Wu Jun Shen Luping Zhou Chen Cai School of Computing and Information Technology University of WollongongNSW 2522Australia SMART Infrastructure Facility University of WollongongNSW 2522Australia School of Civil Mining and EnvironmentalUniversity of WollongongNSW 2522Australia Department of Computer Science and Engineering Hong Kong University of Science and TechnologyHong Kong 999077China Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of ChinaChengdu 611731China School of Electrical and Information Engineering University of SydneyNSW 2006Australia CSIRO’s Data61 NSW 2015Australia

With advanced artificial intelligence and deep learning techniques, a growing number of data sources are playing more and more critical roles in planning and operating transportation services. The General Transit Feed Specification (GTFS), with standard open-source data in both static and real-time formats, is being widely used in public transport planning and operation management. However, compared to other extensively studied data sources such as smart card data and GPS trajectory data, the GTFS data lacks proper investigation yet. Utilization of the GTFS data is challenging for both transport planners and researchers due to its difficulty and complexity of understanding, processing, and leveraging the raw data. In this paper, a GTFS data acquisition and processing framework is proposed to offer an efficient and effective benchmark tool for converting and fusing the GTFS data to a ready-to-use format. To validate and test the proposed framework, a multivariate multistep Long Short-Term Memory is developed to predict train delay with minor anomaly in Sydney as a case study. The contribution of this new framework will render great potential for broader applications and deeper research.

关键词： General transit feed specification Delay prediction Train delay Long short-term memory Data fusion

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Tenacity prediction of polyester materials based on an ensemble soft measurement model

Tenacity prediction of polyester materials based on an ensem...

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2024 China Automation Congress, CAC 2024

作者： Duan, Jiaxu Wang, Jun Tao, Youji Ma, Zhiping Wu, Xin Hu, Zhou State Key Laboratory of Environmental Adaptability for Industrial Products China National Electric Apparatus Research Institute Co. Ltd Guangzhou China Kinte Materials Science and Technology Co. Ltd Guangzhou China Department of Computer Science Hunan University of Technology and Business Changsha China School of Electronic Information and Electrical Engineering Yangtze University Jingzhou China

ISBN: (纸本)9798350368604

In the development process of polyester powder coating materials, it has great guiding significance for the development of new materials as the polyester material properties can be predicted through the given monomer structure and formula. In order to meet the requirements of rapid development of polyester materials, this paper establishes a prediction method based on an ensemble soft measurement model (ESM) for one key property-tenacity in prompting the acceleration of development cycle of polyester products. The processed data employed to train and test the model were collected from a local material company, and it covers over 100 kinds of polymerized resins. Firstly, the molecular expressions of monomers are converted to SMILES codes and further translated to ECFP fingerprints. Then, the principal component analysis (PCA) method is adopted to extract the elements with higher importance in each fingerprint. Finally, the ensemble model that consists of 4 machine learning models was established to make the multi-classification decision in tenacity prediction. The effectiveness of the prediction model is evaluated by comparing the predicted and the practical tensile test results. The results demonstrate that this approach achieves better performance in the material property prediction as well as generalization capability. © 2024 IEEE.

关键词： Tensile testing

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Multi-Layer Network Formation Through HAPS Base Station and Transmissive RIS-Equipped UAV

Multi-Layer Network Formation Through HAPS Base Station and ...

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2025 IEEE Wireless Communications and Networking Conference, WCNC 2025

作者： Khennoufa, Faical Abdellatif, Khelil Yanikomeroglu, Halim Ozturk, Metin Elganimi, Taissir Kara, Ferdi Rabie, Khaled El-Oued University Lgeere Lab Department of Electrical Engineering El-Oued Algeria Carleton University Ntn Lab Department of Systems and Computer Engineering Ottawa Canada Ankara Yildirim Beyazit University Electrical and Electronics Engineering Ankara Turkey University of Tripoli Department of Electrical and Electronic Engineering Libya Kth Royal Institute of Technology Division of Communications Systems Sweden Zonguldak Bulent Ecevit University Department of Computer Engineering Zonguldak Turkey Department of Computer Engineering Center for Communication Systems and Sensing Dhahran Saudi Arabia

ISBN: (纸本)9798350368369

In order to bolster future wireless networks, there has been a great deal of interest in non-terrestrial networks, especially aerial platforms including high-altitude platform stations (HAPS) and uncrewed aerial vehicles (UAVs). These platforms can integrate advanced technologies such as reconfigurable intelligent surfaces (RIS) and non-orthogonal multiple access (NOMA). In this regard, this paper proposes a multi-layer network architecture consisting of HAPS and UAV, where the former acts as a HAPS super macro base station (HAPS-SMBS), while the latter serves as a relay node for the ground Internet of Things (IoT) devices. The UAV is equipped with active transmissive RIS, which is a novel technology with promising benefits. We also utilize multiple-input single-output (MISO) technology, i.e., multiple antennas at the HAPS-SMBS and a single antenna at the IoT devices. Additionally, we consider NOMA as the multiple access technology as well as the existence of hardware impairments as a practical limitation. We compare the proposed system model with various scenarios, all involving the HAPS-SMBS and RIS-equipped UAV relay combination, but with different types of RIS, antenna configurations, and access technologies. Sum rate and energy efficiency are used as performance metrics, and the findings demonstrate that, in comparison to all benchmarks, the proposed system yields significant performance gains. Moreover, hardware impairment limits the system performance at high transmit power levels. © 2025 IEEE.

关键词： Enterprise resource planning

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A Mixed Integer Linear Program for Post-translational Modification Characterization

A Mixed Integer Linear Program for Post-translational Modifi...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Lai, Shengzhi Zhao, Peize Li, Ning Yu, Weichuan The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong The Hong Kong University of Science and Technology Interdisciplinary Programs Office Hong Kong Hkust Shenzhen-Hong Kong Collaborative Innovation Research Institute Futian Shenzhen China The Hong Kong University of Science and Technology Division of Life Science Hong Kong

ISBN: (纸本)9798350386226

Characterizing post-translational modifications (PTMs) is crucial due to their vital role in regulating cellular activities. Current database search methods for peptide identification and PTM characterization face the challenge of exponentially increasing number of PTM combinations. Consequently, these methods resort to enumerating a small fraction of the PTM combinations. However, based on our analysis, more than 99% of the PTM combinations (up to three PTMs) are infeasible as their total mass does not match the mass shift between the precursor mass and theoretical mass. Enumerating those infeasible combinations is unnecessary and would lead to unsatisfactory performance. To address this issue, we propose a two-step method for characterizing multiple PTMs with a reduced search space of feasible PTM combinations only. The method first uses a mixed integer linear program (MILP) to collect feasible peptide sequences and PTM mass combinations. Then, these feasible peptides are exhaustively examined to find the optimal one. We conducted comprehensive experiments to evaluate the method's performance. When applied to a soybean data set, our method has better performance than a representative tag-based search engine. The effectiveness of search space reduction and the sensitivity and precision of our method are demonstrated. © 2024 IEEE.

关键词： Mixed-integer linear programming

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Linear Stability Analysis for a Class of Consensus Controls with Time Delays of Cumulative Distribution Type

Linear Stability Analysis for a Class of Consensus Controls ...

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SICE Annual Conference

作者： Hirokazu Komatsu Hiroshi Yokota Futa Sato Hiroyuki Nakajima General Education Division Faculty of Engineering Kindai University Hiroshima Japan Graduate School of Human and Environmental Studies Kyoto University Kyoto Japan Department of Electrical and Electronic Information Engineering Toyohashi University of Technology Aichi Japan Graduate School of Systems Engineering Kindai University Hiroshima Japan

ISBN: (数字)9784907764838

ISBN: (纸本)9798331544461

We consider consensus control of a multi-agent system with transmission delays, the dynamics of which is described by a linear delay differential equation (LDDE). The transmission time delays we assume are described by a cumulative distribution function, which includes discrete and distributed time delays. Using Tutte's matrix-tree theorem, we show that the zero is a simple root of the characteristic equation derived from the LDDE if and only if the communication graph of the system has a spanning tree. Together with general linear stability theory for DDEs, we also prove the condition that the graph has a spanning tree guarantees the achievement of consensus, that is, all state variables of the LDDE converge to the same constant.

关键词： Sufficient conditions Delay effects Consensus control Numerical simulation Stability analysis Mathematical models Iron Delays Numerical stability Multi-agent systems

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