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arXiv 2024年

作者： Pei, Yingjie Yue, Xinwei Yi, Wenqiang Liu, Yuanwei Li, Xuehua Ding, Zhiguo Key Laboratory of Information and Communication Systems Ministry of Information Industry Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom Department of Electrical Engineering Princeton University Princeton United States School of Electrical and Electronic Engineering The University of Manchester Manchester United Kingdom

Reconfigurable intelligent surface (RIS) has been regarded as a promising technology since it has ability to create the favorable channel conditions. This paper investigates the secure communications of RIS assisted non-orthogonal multiple access (NOMA) networks, where both external and internal eavesdropping scenarios are taken into consideration. More specifically, novel approximate and asymptotic expressions of secrecy outage probability (SOP) for the k-th legitimate user (LU) are derived by invoking imperfect successive interference cancellation (ipSIC) and perfect successive interference cancellation (pSIC). To characterize the secrecy performance of RIS-NOMA networks, the diversity order of the k-th LU with ipSIC/pSIC is obtained in the high signal-to-noise ratio region. The secrecy system throughput of RIS-NOMA networks is discussed in delay-limited transmission mode. Numerical results are presented to verify theoretical analysis that: i) The SOP of RIS-NOMA networks is superior to that of RIS assisted orthogonal multiple access (OMA) and conventional cooperative communication schemes;ii) As the number of reflecting elements increases, the RIS-NOMA networks are capable of achieving the enhanced secrecy performance;and iii) The RIS-NOMA networks have better secrecy system throughput than that of RIS-OMA networks and conventional cooperative communication schemes. Copyright © 2024, The Authors. All rights reserved.

关键词： Cooperative communication

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Optimizing Generative AI Networking: A Dual Perspective with Multi-Agent systems and Mixture of Experts

arXiv

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arXiv 2024年

作者： Zhang, Ruichen Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui Zhang, Ping Kim, Dong In The College of Computing and Data Science Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications China The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

In the continued development of next-generation networking and artificial intelligence content generation (AIGC) services, the integration of multi-agent systems (MAS) and the mixture of experts (MoE) frameworks is becoming increasingly important. Motivated by this, this article studies the contrasting and converging of MAS and MoE in AIGC-enabled networking. First, we discuss the architectural designs, operational procedures, and inherent advantages of using MAS and MoE in generative AI to explore its functionality and applications fully. Next, we review the applications of MAS and MoE frameworks in content generation and resource allocation, emphasizing their impact on networking operations. Subsequently, we propose a novel multi-agent-enabled MoE-proximal policy optimization (MoE-PPO) framework for 3D object generation and data transfer scenarios. The framework uses MAS for dynamic task coordination of each network service provider agent and MoE for expert-driven execution of respective tasks, thereby improving overall system efficiency and adaptability. The simulation results demonstrate the effectiveness of our proposed framework and significantly improve the performance indicators under different network conditions. Finally, we outline potential future research directions. © 2024, CC BY.

关键词： Multi agent systems

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FeReX: A Reconfigurable Design of Multi-bit Ferroelectric Compute-in-Memory for Nearest Neighbor Search

arXiv

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arXiv 2024年

作者： Xu, Zhicheng Liu, Che-Kai Li, Chao Mao, Ruibin Yang, Jianyi Kämpfe, Thomas Imani, Mohsen Li, Can Zhuo, Cheng Yin, Xunzhao Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Zhejiang University Hangzhou China School of Electrical and Computer Engineering Georgia Institute of Technology United States Center Nanoelectric Technologies Fraunhofer IPMS Dresden Germany Department of Computer Science University of California Irvine United States Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province Hangzhou China

Rapid advancements in artificial intelligence have given rise to transformative models, profoundly impacting our lives. These models demand massive volumes of data to operate effectively, exacerbating the data-transfer bottleneck inherent in the conventional von-Neumann architecture. Compute-in-memory (CIM), a novel computing paradigm, tackles these issues by seamlessly embedding in-memory search functions, thereby obviating the need for data transfers. However, existing non-volatile memory (NVM)-based accelerators are application specific. During the similarity based associative search operation, they only support a single, specific distance metric, such as Hamming, Manhattan, or Euclidean distance in measuring the query against the stored data, calling for reconfigurable in-memory solutions adaptable to various applications. To overcome such a limitation, in this paper, we present FeReX, a reconfigurable associative memory (AM) that accommodates various distance metrics including Hamming, Manhattan, and Euclidean distances. Leveraging multibit ferroelectric field-effect transistors (FeFETs) as the proxy and a hardware-software co-design approach, we introduce a constrained satisfaction problem (CSP)-based method to automate AM search input voltage and stored voltage configurations for different distance based search functions. Device-circuit co-simulations first validate the effectiveness of the proposed FeReX methodology for reconfigurable search distance functions. Then, we benchmark FeReX in the context of k-nearest neighbor (KNN) and hyperdimensional computing (HDC), which highlights the robustness of FeReX and demonstrates up to 250× speedup and 104 energy savings compared with GPU. Copyright © 2024, The Authors. All rights reserved.

关键词： Nearest neighbor search

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Cognitive-inspired Post-processing of optical character recognition for Swedish addresses

Cognitive-inspired Post-processing of optical character reco...

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IEEE International Conference on Cognitive Informatics

作者： Moa Andersson Summrina Kanwal Faiza Khan School of Electrical Engineering and Computer Science Kth Royal Institute of Technology in Stockholm Sweden School of Electrical Engineering and Computer Science Kth Royal Institute of Technology in Stockholm Centre for Applied Intelligent Systems Research Halmstad University Sweden Faculty of Computing Riphah International University Islamabad Pakistan

Optical character recognition (OCR) has many ap-plications, such as digitizing historical documents, automating processes, and helping visually impaired people read. However, extracting text from images into a digital format is not an easy problem to solve, and the outputs from the OCR frameworks often include errors. The complexity comes from the many variations in (digital) fonts, handwriting, lighting, etc. To tackle this problem, this thesis investigates two different methods for correcting the errors in OCR output. The used dataset consists of Swedish addresses. The methods are therefore applied to postal automation to investigate the usage of these methods for further automating postal work by automatically reading addresses on parcels using OCR. The first method, the lexical implementation, uses a dataset of Swedish addresses so that any valid address should be in this dataset (hence there is a known and limited vocabulary), and misspelled addresses are corrected to the address in the lexicon with the smallest Levenshtein distance. The second approach uses the same dataset, but with artificial errors, or artificial noise, added. The addresses with this artificial noise are then used together with their correct spelling to train a machine learning model based on Neural machine translation (NMT) to automatically correct errors in OCR read addresses. The results from this study could contribute by defining in what direction future work connected to OCR and postal addresses should go. The results were that the lexical implementation outperformed the NMT model. However, more experiments including real data would be required to draw definitive conclusions as to how the methods would work in real-life applications.

关键词： Vocabulary Automation Computational modeling Optical character recognition Lighting Machine learning Complexity theory

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Feedback control in RF photonic transversal filter systems based on optical microcombs

Feedback control in RF photonic transversal filter systems b...

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CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Li, Yang Wu, Jiayang Sun, Yang Ren, Guanghui Tan, Mengxi Xu, Xingyuan Corcoran, Bill Chu, Sai Tak Little, Brent E. Morandotti, Roberto Mitchell, Arnan Moss, David J. Optical Sciences Centre Swinburne University of Technology HawthornVIC3122 Australia Integrated Photonics and Applications Centre School of Engineering RMIT University MelbourneVIC3000 Australia School of Electronic and Information Engineering Beihang University Beijing100191 China State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing100876 China Photonic Communications Laboratory Dept. Electrical and Computer Systems Engineering Monash University ClaytonVIC Australia Department of Physics City University of Hong Kong Hong Kong QXP Technology Inc. Xi'an China INRS - Énergie Matériaux et Télécommunications VarennesQCJ3X 1S2 Canada

We propose and experimentally demonstrate four different feedback control methods employed in microcomb-based RF photonic transversal filter systems to enhance their accuracy and stability. Detailed characterizations ... 详细信息

关键词： Transversal filters

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Hand Gesture Recognition from an Open-Set Perspective

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IEEE Transactions on Multimedia 2025年

作者： Zhou, Jun Xu, Chi Cheng, Li China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Vision and Learning Laboratory Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada

Existing hand gesture recognition methods predominantly rely on a close-set assumption, which in essence limits the viewpoints, gesture categories, and hand shapes at test time to closely resemble those seen during training. This requirement is however rarely met in practice, as images are often captured from unconstrained viewpoints, with novel gestures and unseen hand shapes that can differ significantly from the training data. This motivates us to investigate an open-set hand gesture recognition problem, where hand gestures are still recognizable from unconstrained viewpoints, and novel gesture classes and hand shapes can be incrementally learned with just a few examples. To address this, we propose a viewpoint influence elimination network that extracts view-independent features, significantly improving performance in scenarios with unconstrained viewpoints. Moreover, a joint-weighted classification scheme is introduced to augment the cosine similarity metric for evaluating few-shot incremental learning of novel gestures and shapes. Finally, as existing hand gesture recognition datasets primarily adhere to the close-set assumption, a new hand gesture recognition dataset, OHG, is introduced in this paper, that includes a wide range of viewpoints, diverse gesture classes, and distinct hand shapes. Experimental hand gesture recognition results demonstrate the superior performance of our approach in both unconstrained viewpoint and few-shot incremental learning scenarios. The source code and the OHG dataset are to be made available at https://***/zhoujun-7/OSHGR. © 1999-2012 IEEE.

关键词： Palmprint recognition

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FIRE: a dataset for feedback integration and refinement evaluation of multimodal models 24

FIRE: a dataset for feedback integration and refinement eval...

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Proceedings of the 38th International Conference on Neural Information Processing systems

作者： Pengxiang Li Zhi Gao Bofei Zhang Tao Yuan Yuwei Wu Mehrtash Harandi Yunde Jia Song-Chun Zhu Qing Li Beijing Key Laboratory of Intelligent Information Technology School of Computer Science & Technology Beijing Institute of Technology and State Key Laboratory of General Artificial Intelligence BIGAI State Key Laboratory of General Artificial Intelligence BIGAI and State Key Laboratory of General Artificial Intelligence Peking University State Key Laboratory of General Artificial Intelligence BIGAI Beijing Key Laboratory of Intelligent Information Technology School of Computer Science & Technology Beijing Institute of Technology and Guangdong Laboratory of Machine Perception and Intelligent Computing Shenzhen MSU-BIT University Department of Electrical and Computer System Engineering Monash University Guangdong Laboratory of Machine Perception and Intelligent Computing Shenzhen MSU-BIT University and Beijing Key Laboratory of Intelligent Information Technology School of Computer Science & Technology Beijing Institute of Technology State Key Laboratory of General Artificial Intelligence BIGAI and State Key Laboratory of General Artificial Intelligence Peking University and Department of Automation Tsinghua University

ISBN: (纸本)9798331314385

Vision language models (VLMs) have achieved impressive progress in diverse applications, becoming a prevalent research direction. In this paper, we build FIRE, a feedback-refinement dataset, consisting of 1.1M multi-turn conversations that are derived from 27 source datasets, empowering VLMs to spontaneously refine their responses based on user feedback across diverse tasks. To scale up the data collection, FIRE is collected in two components: FIRE-100K and FIRE-1M, where FIRE-100K is generated by GPT-4V, and FIRE-1M is freely generated via models trained on FIRE-100K. Then, we build FIRE-Bench, a benchmark to comprehensively evaluate the feedback-refining capability of VLMs, which contains 11K feedback-refinement conversations as the test data, two evaluation settings, and a model to provide feedback for VLMs. We develop the FIRE-LLaVA model by fine-tuning LLaVA on FIRE-100K and FIRE-1M, which shows remarkable feedback-refining capability on FIRE-Bench and outperforms untrained VLMs by 50%, making more efficient user-agent interactions and underscoring the significance of the FIRE dataset.

关键词：

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Distributed Adaptive Fault-Tolerant Output Regulation of Heterogeneous Multi-Agent systems With Coupling Uncertainties and Actuator Faults

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IEEE/CAA Journal of Automatica Sinica 2020年第4期7卷 1098-1106页

作者： Chao Deng Weinan Gao Weiwei Che the School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore the Department of Electrical and Computer Engineering Allen E.Paulson College of Engineering and ComputingGeorgia Southern UniversityStatesboroGA 30460 USA the State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang UniversityHangzhou 310027 the Institute of Complexity Science Qingdao UniversityQingdao 266071China

In this paper, we consider the distributed adaptive fault-tolerant output regulation problem for heterogeneous multiagent systems with matched system uncertainties and mismatched coupling uncertainties among subsystems under the influence of actuator faults. First, distributed finite-time observers are proposed for all subsystems to observe the state of the exosystem. Then, a novel fault-tolerant controller is designed to compensate for the influence of matched system uncertainties and actuator faults. By using the linear matrix inequality technique, a sufficient condition is provided to guarantee the solvability of the considered problem in the presence of mismatched coupling uncertainties. Moreover, it is shown that the system in closed-loop with the developed controller can achieve output regulation by using the Lyapunov stability theory and cyclic-small-gain ***, a numerical example is given to illustrate the effectiveness of the obtained result.

关键词： Adaptive control cyclic-small-gain fault-tolerant control multi-agent systems(MASs)

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Hierarchical Recording Architecture for Three-Dimensional Magnetic Recording

arXiv

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arXiv 2025年

作者： Jian, Yugen Luo, Ke Chen, Jincai Fong, Xuanyao Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan430074 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore School of Computer of Science and Technology Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Information Storage System Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China Wuhan430074 China

Three-dimensional magnetic recording (3DMR) is a highly promising approach to achieving ultra-large data storage capacity in hard disk drives. One of the greatest challenges for 3DMR lies in performing sequential and correct writing of bits into the multi-layer recording medium. In this work, we have proposed a hierarchical recording architecture based on layered heat-assisted writing with a multi-head array. The feasibility of the architecture is validated in a dual-layer 3DMR system with FePt-based thin films via micromagnetic simulation. Our results reveal the magnetization reversal mechanism of the grains, ultimately attaining appreciable switching probability and medium signal-to-noise ratio (SNR) for each layer. In particular, an optimal head-to-head distance is identified as the one that maximizes the medium SNR. Optimizing the system’s noise resistance will improve the overall SNR and allow for a smaller optimal head-to-head distance, which can pave the way for scaling 3DMR to more recording layers. Copyright © 2025, The Authors. All rights reserved.

关键词： Hard disk storage

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Efficient Error-Bounded Lossy Compression for CPU Architectures

Efficient Error-Bounded Lossy Compression for CPU Architectu...

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International Symposium on Modeling, Analysis and Simulation of computer and Telecommunication systems (MASCOTS)

作者： Griffin Dube Jiannan Tian Sheng Di Dingwen Tao Jon C. Calhoun Franck Cappello Department of Computer Science Northwestern University Evanston IL Luddy School of Informatics Computing and Engineering Indiana University Bloomington IN Holcombe Department of Electrical and Computing Engineering Clemson University Clemson SC Mathematics and Computer Science Division Argonne National Laboratory Lemont IL

Modern HPC applications produce increasingly large amounts of data, which limits the performance of current extreme-scale systems. Lossy compression, helps to mitigate this issue by decreasing the size of data generated by these applications. SZ, a current state-of-the-art lossy compressor, is able to achieve high compression ratios, but its prediction/quantization methods contain RAW dependencies that prevent parallelizing this step of the compression. Recent work proposes a parallel dual prediction/quantization algorithm for GPUs which removes these dependencies. However, some HPC systems and applications do not use GPUs, and could still benefit from the fine-grained parallelism of this method. Using the dual-quantization technique, we implement and optimize a SIMD vectorized CPU version of SZ (vecSZ), and create a heuristic for selecting the optimal block size and vector length. We propose a novel block padding algorithm to decrease the number of unpredictable values along compression block borders and find it reduces the number of prediction outliers by up to 100%. We measure performance of our vecSZ against an CPU version of SZ using dual-quantization, pSZ, as well as SZ-1.4. Using real-world scientific datasets, we evaluate vecSZ on the Intel Skylake and AMD Rome architectures. vecSZ results in up to 32% improvement in rate-distortion and up to 15× speedup over SZ-1.4, achieving a prediction and quantization bandwidth in excess of 3.4 GB/s.

关键词： Analytical models Quantization (signal) Computational modeling Rate-distortion computer architecture Bandwidth Prediction algorithms

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