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Optical multipath self-interference cancellation for a wideband in-band full-duplex system using a silicon photonic modulator chip

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Chinese Optics Letters 2024年第7期22卷 126-131页

作者： Xiao Yu Jia Ye Lianshan Yan Tao Zhou Yue Zhu Peng Li Xihua Zou Wei Pan Center for Information Photonics and Communications School of Information Science and TechnologySouthwest Jiaotong UniversityChengdu 611756China Key Laboratory of Electronic Information Control Southwest China Research Institute of Electronic EquipmentChengdu 610029China Microwave Photonics Research Laboratory School of Electrical Engineering and Computer ScienceUniversity of OttawaOttawaONK1N6N5Canada

We propose and experimentally demonstrate a photonic method for wideband multipath self-interference cancellation using a silicon photonic modulator *** chip generates phase-inverted reference signals by leveraging the opposite phase between optical *** managing amplitude and phase imbalances between self-interference and reference signals,the approach rectifies discrepancies through consistent chip manufacturing and packaging *** photonic multi-dimensional multiplexing,including wavelength and polarization,enables the acquisition of multiple reference *** results show multipath cancellation depths of 25.53 dB and 23.81 dB for bandwidths of 500 MHz and 1 GHz,achieved by superimposing 2-path reference signals.

关键词： microwave photonics multipath self-interference silicon photonics

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Multi-level decision framework collision avoidance algorithm in emergency scenarios

arXiv

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arXiv 2023年

作者： Chen, Guoying Wang, Xinyu Hua, Min Liu, Wei State Key Laboratory of Automotive Simulation and Control Jilin University Jilin Changchun China School of Engineering University of Birmingham Birmingham United Kingdom School of Electrical and Computer Engineering Purdue University West Lafayette United States

With the rapid development of autonomous driving, the attention of academia has increasingly focused on the development of anti-collision systems in emergency scenarios, which have a crucial impact on driving safety. While numerous anti-collision strategies have emerged in recent years, most of them only consider steering or braking. The dynamic and complex nature of the driving environment presents a challenge to developing robust collision avoidance algorithms in emergency scenarios. To address the complex, dynamic obstacle scene and improve lateral manoeuvrability, this paper establishes a multi-level decision-making obstacle avoidance framework that employs the safe distance model and integrates emergency steering and emergency braking to complete the obstacle avoidance process. This approach helps avoid the high-risk situation of vehicle instability that can result from the separation of steering and braking actions. In the emergency steering algorithm, we define the collision hazard moment and propose a multi-constraint dynamic collision avoidance planning method that considers the driving area. Simulation results demonstrate that the decision-making collision avoidance logic can be applied to dynamic collision avoidance scenarios in complex traffic situations, effectively completing the obstacle avoidance task in emergency scenarios and improving the safety of autonomous driving. Copyright © 2023, The Authors. All rights reserved.

关键词： Collision avoidance

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Hierarchical Multimodal Decoupling-Fusion Framework for offline Multiple Appropriate Facial Reaction Generation

Hierarchical Multimodal Decoupling-Fusion Framework for offl...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Qincheng Lv Xiaofeng Liu Jie Li Rongrong Ni Pujun Xue Siyang Song College of Information Science and Engineering Hohai University Changzhou China College of Artificial Intelligence and Automation Hohai University Changzhou China School of Biomedical Engineering and Informatics Nanjing Medical University Nanjing China School of Microelectronics and Control Engineering Changzhou University Changzhou China School of Computer Science University of Exeter Exeter U.K.

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Facial reactions convey crucial emotional information and coordinating interpersonal relationships in human dyadic interactions. While existing Multiple Appropriate Facial Reaction Generation (MAFRG) methods focus on generating multiple reasonable facial reactions, none of these approaches combines 2D and 3D facial behaviour information nor account for the influence of individuals’ facial identities, leading to inconsistencies in the generated facial reactions and limited capability in capturing subtle variations in facial depth and expression dynamics. This paper proposes a novel Hierarchical Multimodal Decoupling-Fusion (HMDF) framework that decouples 3D facial identity from expression behaviors, eliminating identity-based interference in the reaction generation process, which are integrated with audio-visual features through a cross-attention mechanism. Experiments show that our framework achieved the enhanced diversity and synchrony in the generated facial reactions.

关键词： Three-dimensional displays Interference Signal processing Acoustics Speech processing

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Direct Data-Driven State-Feedback control of Linear Parameter-Varying Systems

arXiv

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arXiv 2022年

作者： Verhoek, Chris Tóth, Roland Abbas, Hossam S. Control Systems group Dept. of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands Systems and Control Lab Institute for Computer Science and Control Budapest Hungary Institute for Electrical Engineering in Medicine Universität zu Lübeck Lübeck Germany

The framework of linear parameter-varying (LPV) systems has shown to be a powerful tool for the design of controllers for complex nonlinear systems using linear tools. In this work, we derive novel methods that allow to synthesize LPV state-feedback controllers directly from only a single sequence of data and guarantee stability and performance of the closed-loop system. We show that if the measured open-loop data from the system satisfies a persistency of excitation condition, then the full open-loop and closed-loop input-scheduling-state behavior can be represented using only the data. With this representation we formulate data-driven analysis and synthesis problems, where the latter yields controllers that guarantee stability and performance in terms of infinite horizon quadratic cost, generalized H2-norm and 2-gain of the closed-loop system. The controllers are synthesized by solving a semi-definite program. Additionally, we provide a synthesis method to handle noisy measurement data. Competitive performance of the proposed data-driven synthesis methods is demonstrated w.r.t. model-based synthesis in multiple simulation studies, including a nonlinear unbalanced disc system. © 2022, CC BY-NC-SA.

关键词： State feedback

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A Multi-Player Potential Game Approach for Sensor Network Localization with Noisy Measurements

A Multi-Player Potential Game Approach for Sensor Network Lo...

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IEEE Conference on Decision and control

作者： Gehui Xu Guanpu Chen Baris Fidan Yiguang Hong Hongsheng Qi Thomas Parisini Karl H. Johansson Department of Electrical and Electronic Engineering Imperial College London London UK Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Mechanical and Mechatronics Engineering University of Waterloo Waterloo ON Canada Department of Control Science and Engineering Tongji University shanghai China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai China Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing China Department of Electronic Systems Aalborg University Denmark Department of Engineering and Architecture University of Trieste Italy

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Sensor network localization (SNL) is a challenging problem due to its inherent non-convexity and the effects of noise in inter-node ranging measurements and anchor node position. We formulate a non-convex SNL problem as a multiplayer non-convex potential game and investigate the existence and uniqueness of a Nash equilibrium (NE) in both the ideal setting without measurement noise and the practical setting with measurement noise. We first show that the NE exists and is unique in the noiseless case, and corresponds to the precise network localization. Then, we study the SNL for the case with errors affecting the anchor node position and the inter-node distance measurements. Specifically, we establish that in case these errors are sufficiently small, the NE exists and is unique. It is shown that the NE is an approximate solution to the SNL problem, and that the position errors can be quantified accordingly. Based on these findings, we apply the results to case studies involving only inter-node distance measurement errors and only anchor position information inaccuracies.

关键词： Location awareness Noise Games Position measurement Nash equilibrium Distance measurement Noise measurement

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Climate Downscaling Using Neural Operator: Spatiotemporal Multimodal Fusion Operator with State-Query Coupled Kernel

Climate Downscaling Using Neural Operator: Spatiotemporal Mu...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Haodi Zhang Yichi Wang Yifan Jian Jiahui Jiang Zhaohai Bai Lin Ma College of Computer Science and Software Engineering Shenzhen University Center for Agricultural Resources Research Institute of Genetic and Developmental Biology Chinese Academy of Sciences State Key Laboratory of Pollution Control and Resource Reuse School of the Environment Nanjing University

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Climate downscaling is crucial for detailed small- scale analysis and for acquiring climate data in regions without weather stations. Operator learning has proven potential for this task. However, several challenges remain in operator learning, such as multimodal fusion, spatiotemporal fusion and input state and query adaptation. To address these challenges, we propose a Spatiotemporal Multimodal Fusion Operator with a State- Query Coupled Kernel (SMCK). This framework includes a latent space fusion encoder that encodes climate variables using position-wise multihead attention for multimodal fusion and integrates historical information to generate robust and precise representation. Additionally, we introduce a state-query coupled kernel that combines radial basis functions and discrete fourier encoding to enhance query location representation, while also adapting to the state to obtain the coupled kernel. Extensive experiments demonstrate that our method achieves state-of-the-art performance and provides strong support for climate downscaling and the planning of climate-related strategies.

关键词： Couplings Signal processing Encoding Robustness Spatiotemporal phenomena Planning Kernel Speech processing Forecasting Meteorology

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A Bayesian k-vector estimation method for electromagnetic waves in magnetized cold plasma

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URSI Radio Science Bulletin 2023年第378期2021卷 77-82页

作者： Yuji Tanaka Mamoru Ota Shoya Matsuda Yoshiya Kasahara Division of Electrical Engineering Graduate School of Engineering Kyoto University Kyotodaigaku-Katsura Nishikyo-ku Kyoto Kyoto Japan Department of Electrical and Control Systems Engineering National Institute of Technology Toyama College 13 Hongo-machi Toyama Toyama Japan Division of Electrical Engineering and Computer Science Graduate School of Natural Science and Technology Kanazawa University Kakuma Kanazawa Ishikawa Japan

Using the plasma wave characteristics and remote sensing technology, the k-vector direction of plasma waves can provide important information for understanding the global features of space plasma. In this study, we proposed a Bayesian k-vector estimation method in magnetized cold plasma based on the wave distribution function method. The proposed method can be applied to various types of sensors with easy visualization and calculation of the estimation accuracy. We verified the effectiveness of the proposed method through simulations.

关键词： Estimation Plasmas Electromagnetics Mathematical models Magnetic sensors Bayes methods Plasma waves

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Mining Erasable Patterns Using the Bitmap Method in Quantitative Component Databases 17th

Mining Erasable Patterns Using the Bitmap Method in Quantita...

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17th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2025

作者： Hong, Tzung-Pei Chen, Da Huang, Wei-Ming Tsai, Yu-Chuan Department of Computer Science and Information Engineering National University of Kaohsiung Kaohsiung City Taiwan Department of Electrical and Control China Steel Corporation Kaohsiung City Taiwan Library and Information Center National University of Kaohsiung Kaohsiung City Taiwan

ISBN: (纸本)9789819660070

Mining erasable patterns from a database are for applying resources to maximize production with limited funds. Since the concept of erasable pattern mining was proposed, a manager can use it to optimize the production plan effectively. However, real applications have critical factors, such as costs or quantities of material, which traditional methods can not handle. This paper thus considers mining erasable itemsets from a product database with quantitative components. We propose an erasable itemset mining algorithm with the bit-vector manipulation method for quantitative component databases. It extracts raw materials with lower profits by analyzing the relationships between products and materials. In numerical experiments, the real-world and synthetic datasets were used to evaluate the performance in the execution time with different thresholds. Experimental results show that the proposed algorithm performs better than previous work. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Bit-vector method Data mining Erasable itemsets Profit-based mining Quantitative component database

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Using a Separation Approach for the Radiality Constraints in Power Distribution Networks

SSRN

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SSRN 2023年

作者： Geri, Alberto Maccioni, Marco Meloni, Carlo Nati, Ludovico Department of Astronautics Electrical and Energy Engineering Sapienza University of Rome Via Eudossiana 18 Rome00184 Italy Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Rome00185 Italy

Power distribution networks are usually characterized by a radial topology and therefore the related optimization problems involve radiality constraints in their mathematical formulations. This paper considers mixed integer optimization approaches devoted to find an optimal acyclic spanning subgraph subject to both technical side constraints and radiality requirements on a graph representing the distribution network. Our focus is on the combinatorial formulation of radiality constraints and their delayed efficient generation following a separation-optimization scheme. Computational experiments on benchmarks from the literature are used to illustrate and validate the proposed approach. © 2023, The Authors. All rights reserved.

关键词： Combinatorial optimization

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Partial Discharge Classification With 1D Convolutional Neural Network

Partial Discharge Classification With 1D Convolutional Neura...

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International Conference on Properties and Applications of Properties and Applications of Dielectric Materials

作者： Thepjit Cheypoca Wiboon Promphanich Aung Ye Thway Angelina Phimpissada Hankae Siwakorn Jeenmuang Norasage Pattanadech Instrumentation and Control Engineering Dept. School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Computer Engineering Dept. School of EngineeringKing Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Electrical Engineering Dept. School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Mechatronics Engineering Dept. School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand

ISBN: (数字)9798350374605

ISBN: (纸本)9798350386165

This paper introduces a novel approach for classifying with the 1D Convolutional Neural Network model for partial discharge patterns, that consists of corona discharge, surface discharge and internal discharge. The PD measuring circuit suggested in IEC 60270:2000 is used to record Partial discharge signals. Independent parameters such as phase and charge of PD patterns were recorded. The Artificial Neural Network for the classification model was constructed. Moreover, 2×1D CNN feature extraction was utilized to reduce the curse of dimensionality in the dense layer of the proposed PD classification model. 80% of the recorded data will be used as a training data and 20% recorded data was used for testing of the classification models. Impacts of neuron numbers and network architecture on the PD classification performance will be observed.

关键词： Partial discharges Partial discharge measurement Surface discharges Neurons Training data Discharges (electric) Data models Convolutional neural networks Integrated circuit modeling Testing

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