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检索条件"主题词=Signal Processing Algorithms"

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Orthogonal Matching Pursuit-Based algorithms for the Birkhoff-Von Neumann Decomposition

Orthogonal Matching Pursuit-Based Algorithms for the Birkhof...

引用

European signal processing Conference (EUSIPCO)

作者： Damien Lesens Jérémy E. Cohen Bora Uçar LIP ENS de Lyon 46 allée d'Italie Lyon France Univ Lyon INSA-Lyon UCBL UJM CNRS Inserm CREATIS UMR 5220 U1294 Lyon France CNRS and LIP UMR5668 (Université de Lyon - ENS de Lyon - UCBL - CNRS - Inria) 46 allée d'Italie Lyon France

ISBN: (数字)9789464593617

ISBN: (纸本)9798331519773

Birkhoff-von Neumann (BvN) decomposition writes a doubly stochastic matrix as a convex combination of permutation matrices. For a given doubly stochastic matrix, the decom-position in general is not unique. In many applications a sparsest decomposition, that is with the smallest number of permutation matrices is of interest. This problem is known to be NP-complete, and heuristics are used to obtain sparse solutions. We propose heuristics based on the well-known orthogonal matching pursuit for sparse BvN decomposition. We experimentally compare our heuristics with the state of the art from the literature and show how our methods advance the known heuristics.

关键词： Heuristic algorithms Matching pursuit algorithms signal processing algorithms Europe signal processing Matrix decomposition Sparse matrices Optimization

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Towards Neuromorphic processing for Next-Generation MU-MIMO Detection

Towards Neuromorphic Processing for Next-Generation MU-MIMO ...

引用

IEEE Workshop on signal processing Advances in Wireless Communications (SPAWC)

作者： G. N. Katsaros J. C. De Luna Ducoing Konstantinos Nikitopoulos 5GIC & 6GIC Institute for Communication Systems (ICS) University of Surrey Guildford UK

ISBN: (数字)9798350393187

ISBN: (纸本)9798350393194

Upcoming physical layer (PHY) processing solutions, leveraging multiple-input multiple-output (MIMO) advances, are expected to support broad transmission bandwidths and the concurrent transmission of multiple information streams. However, the inherent computational complexities of conventional MIMO PHY algorithms pose significant practical challenges, not only in meeting the strict real-time processing latency requirements but also in maintaining practical computational power consumption budgets. Novel computing paradigms, such as neuromorphic computing, promise substantial gains in computational power efficiency. However, it is unknown whether it is feasible or efficient to realize practical PHY algorithms on such platforms. In this work, we evaluate for the first time the potential of neuromorphic computing principles for multi-user (MU)-MIMO detection. In particular, we developed the first spiking-based MU-MIMO simulator that meets practical error-rate targets, suggesting power gains of at least one order of magnitude when realized on actual neuromorphic hardware, compared to conventional processing platforms. Finally, we discuss the challenges and future research directions that could unlock practical neuromorphic-based MU-MIMO systems and revolutionize PHY power efficiency.

关键词： Wireless communication Power demand Neuromorphic engineering Neural networks signal processing algorithms signal processing Physical layer Real-time systems Streams Next generation networking

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The ESPRIT Algorithm Under High Noise: Optimal Error Scaling and Noisy Super-Resolution

The ESPRIT Algorithm Under High Noise: Optimal Error Scaling...

引用

Annual IEEE Symposium on Foundations of Computer Science

作者： Zhiyan Ding Ethan N. Epperly Lin Lin Ruizhe Zhang UC Berkeley Caltech Lawrence Berkeley National Laboratory UC Berkeley Simons Institute

ISBN: (数字)9798331516741

ISBN: (纸本)9798331516758

Subspace-based signal processing techniques, such as the Estimation of signal Parameters via Rotational Invariant Techniques (ESPRIT) algorithm, are popular methods for spectral estimation. These algorithms can achieve the so-called super-resolution scaling under low noise conditions, surpassing the well-known Nyquist limit. However, the performance of these algorithms under high-noise conditions is not as well understood. Existing state-of-the-art analysis indicates that ESPRIT and related algorithms can be resilient even for signals where each observation is corrupted by statistically independent, mean-zero noise of size $\mathcal{O}(1)$ , but these analyses only show that the error $\epsilon$ decays at a slow rate $\epsilon=\widetilde{\mathcal{O}}(n^{-1/2})$ with respect to the cutoff frequency $n$ (i.e., the maximum frequency of the measurements). In this work, we prove that under certain assumptions, the ESPRIT algorithm can attain a significantly improved error scaling $\epsilon=\widetilde{\mathcal{O}}(n^{-3/2})$ , exhibiting noisy super-resolution scaling beyond the Nyquist limit $\epsilon=\mathcal{O}(n^{-1})$ given by the Nyquist-Shannon sampling theorem. We further establish a theoretical lower bound and show that this scaling is optimal. Our analysis introduces novel matrix perturbation results, which could be of independent interest.

关键词： Perturbation methods Superresolution Noise Cutoff frequency Measurement uncertainty signal processing algorithms Estimation Size measurement Frequency measurement Noise measurement

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Applying Artificial Bee Colony Algorithm to Improve UWSNs Communication

Applying Artificial Bee Colony Algorithm to Improve UWSNs Co...

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Communication, Computing and signal processing (IICCCS), IEEE International Conference on

作者： Mohammed I. Habelalmateen Amandeep Kaur Annapurnanand Tiwari Shalini M Melvin Victor Neelam Sanjeev Kumar Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Computers Techniques Engineering College of Technical Engineering The Islamic University of Al Diwaniyah Al Diwaniyah Iraq Department of Computer Science Engineering Chandigarh Engineering College Chandigarh Group of Colleges Mohali Punjab India Department of Electronics & Communication Engineering IES College of Technology Bhopal M.P. India Prince Shri Venkateshwara Padmavathy Engineering College Chennai India School of Business and Management Christ (Deemed to be University) Department of Computer Science & Engineering (E.Tech.) SRM Institute of Science & Technology Chennai

ISBN: (数字)9798350390759

ISBN: (纸本)9798350390766

The research in this study aims at implementing the ABC algorithm to enhance the communication within UWSNs. The ABC algorithm, motivated by the CPG approach being analogous to that of honey bees searching for food, specifies optimal values for critical parameters of the network such as energy consumption, reliability in data transfer, and scalability. From the analyses conducted in this exposition, it is apparent that the envisaged methodology outperforms other conventional routing parlances in the following ways: minimal energy usage, high data delivery ratios, low packet drops, and longest network lifetime. Therefore, from the above results it can be concluded that, the said ABC algorithm is helping in achieving a better result in terms of improved underwater communication as well as in mitigating with the difficulties of UWSNs.

关键词： Wireless communication Wireless sensor networks Underwater communication Scalability signal processing algorithms signal processing Artificial bee colony algorithm Routing Robustness Telecommunication computing

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Research on Distribution Path Optimization of Warehousing Management System Based on Simulated Annealing Algorithm

Research on Distribution Path Optimization of Warehousing Ma...

引用

signal processing, Communications and Engineering Management Conference (ISPCEM), International

作者： Tan Meng Guangxi Vocational Normal University Nanning China

ISBN: (数字)9798331528676

ISBN: (纸本)9798331528683

This research applies the simulated annealing algorithm within a logistics warehousing system to address the inherent complexity and unpredictability of optimizing distribution routes. By devising an appropriate algorithmic framework and incorporating the specific logistics demands alongside the warehousing layout, this paper establishes a model for optimizing distribution paths. The model is then validated through the application of computer-based simulation techniques. Throughout the simulation, the system dynamically adjusts the distribution routes according to varying logistics scenarios and delivery requirements, ultimately producing optimized results across different conditions. The simulation outcomes demonstrate that the simulated annealing algorithm performs efficiently in resolving distribution route optimization challenges, yielding substantial improvements in both route distance and delivery times. The results from the data analysis indicate that the path optimized using the simulated annealing algorithm outperforms conventional methods across several critical metrics, including overall distance traveled and time required. These findings confirm the practical viability and enhanced effectiveness of the algorithm when applied to real-world scenarios, demonstrating its superior performance compared to traditional approaches. The algorithm's ability to achieve better optimization in key performance indicators further substantiates its applicability and success in distribution path optimization tasks.

关键词： Data analysis Heuristic algorithms Computational modeling Warehousing Layout signal processing algorithms Simulated annealing Complexity theory Optimization Logistics

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A Framework for Mining and Applying Alarm Rules Based on LLM

A Framework for Mining and Applying Alarm Rules Based on LLM

引用

International Conference on Vision, Image and signal processing (ICVISP)

作者： Guoqing Li Qian Zhang Haijun Su Mengyuan Zhu Mengqi Liu Haokai Zhang Development Center China Information Technology Designing & Consulting Institute Co. Ltd Beijing China

ISBN: (数字)9798331541460

ISBN: (纸本)9798331541477

Driven by 5G technology, network performance and management requirements are becoming increasingly sophisticated. However, massive and complex alarm information is also coming, posing severe challenges to network operation and maintenance. Accurately identifying alarm correlations and locating alarm root causes has become a core problem for operation and maintenance. In response to this challenge, this paper proposes a framework for mining and applying alarm rules based on large language models, which applies the text understanding capabilities of large language models to alarm processing and can mine uncommon alarm rules. Experimental results show that this framework significantly improves the accuracy and coverage of alarm rules, and improves the response speed and efficiency of network operation and maintenance.

关键词： Technological innovation Correlation Large language models Knowledge based systems signal processing algorithms signal processing Real-time systems Maintenance Communication networks Optimization

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Diagonal Loading Method with Small Snapshot Number and Steering Vector Errors

Diagonal Loading Method with Small Snapshot Number and Steer...

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IEEE International Conference on Information Communication and signal processing (ICICSP)

作者： Feixue Yang Wen Ren Zhenyu Zhang Linlin Sun School of Electronic Engineering and Optical Engineering Nanjing University of Science and Technology Nanjing China Space star technology co. LTD Beijing China

ISBN: (数字)9798350355895

ISBN: (纸本)9798350355901

Diagonal loading is often used to improve the robustness of beamforming algorithms as a classic method. In this paper, two classic diagonal loading algorithms are first discussed respectively for the case of small number of snapshots and for the case of steering vector errors, and then they are combined to improve the performance of the original algorithms, and the formulas for the joint algorithm are given. Computer simulation results show that the joint method can expand the applicability of the two algorithms at the steering vector error level, so that the signal-to-interference-noise ratio of the array output maintains good performance within a larger range of standard deviations of the steering vector. Secondly, the combined method can compensate for the limitation of the small range of scale factor values in the steering vector errors variance loading method, reduce the possibility of adverse consequences caused by improper scale factor values, and improve the robustness of the algorithm.

关键词： Array signal processing Computer simulation Loading signal processing algorithms Vectors Robustness Standards signal to noise ratio

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Overview of Load Disaggregation Models, Methods and Hardware

Overview of Load Disaggregation Models, Methods and Hardware

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International Universities Power Engineering Conference (UPEC)

作者： Mircea N. Lancranjan Alexandru Muresan Dacian I. Jurj Alexandru Berciu Alexis Polycarpou Levente Czumbil Dan D. Micu Department Electrical Engineering Technical University of Cluj-Napoca Cluj-Napoca Faculty of Automation and Computer Science Technical University of Cluj-Napoca Cluj-Napoca Department of Electrical and Computer Engineering and Informatics Frederick University Nicosia Cyprus

ISBN: (数字)9798350379730

ISBN: (纸本)9798350379747

In the dynamic landscape of energy efficiency, a domain garnering ever increasing attention and urgency, the cornerstone of informed decision-making resides in the acquisition of reliable data. This paper summarizes the main approaches, methods and hardware used to gather, process and disaggregate such data on an appliance-by-appliance basis. The paper explores a critical analysis of the various models and techniques that support the gathering of energy data at the appliance level. A range of approaches, including hardware-based solutions such as smart meters, submeters, and sensor arrays, placing a special focus on intrusive load monitoring (ILM) and non-intrusive load monitoring (NILM) algorithms that employ advanced signal processing and machine learning techniques, are examined for their effectiveness, scalability, and suitability for both industrial and commercial contexts. Furthermore, the challenges of data acquisition capabilities, reconciling scalability, cost-effectiveness, and user-friendliness - prerequisites for widespread acceptance and uptake are also investigated.

关键词： Load monitoring Costs Scalability signal processing algorithms Hardware Smart meters Energy efficiency Transient analysis Time complexity Load modeling

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Content Update via Deep Reinforcement Learning in Recommendation-Aware Edge Caching Network

Content Update via Deep Reinforcement Learning in Recommenda...

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6th International Conference on Intelligent Computing and signal processing (ICSP)

作者： Ze Qiao Quan Yu Wuhan University of Technology

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

In this paper, we propose a cache update strategy in recommendation-aware wireless edge caching networks, aiming to alleviate network transmission burden and enhance user experience. We model user request behavior as a continuous recommendation-driven request process, rather than assuming users follow a single request probability distribution. This model makes user request behavior closer to real-world scenarios and assists the base station in making more accurate update strategy. We focus on changes in cache hit rate and similarity before and after updates, and formulate them into a cache update optimization problem. To solve this problem, we propose a cache update algorithm based on deep reinforcement learning (DRL), which can make update decisions based on users' historical requests and contents cached in base stations. Simulation results demonstrate that the proposed algorithm outperforms some traditional algorithms in both content recommendation and cache update aspects.

关键词： Wireless communication Measurement Base stations Simulation signal processing algorithms signal processing Deep reinforcement learning User experience Probability distribution Optimization

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A High-Precision Direction Finding Method Assisted by Multipoint Ranging Sequences

A High-Precision Direction Finding Method Assisted by Multip...

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IEEE International Conference on signal processing, Communications and Computing (ICSPCC)

作者： Yangyang Liu Tianyu Li Yuan Zhao Chengkai Tang Zesheng Dan Yankang Bai School of Electronics and Information Northwestern Polytechnical University Xi'an China

ISBN: (数字)9798350366556

ISBN: (纸本)9798350366563

The positioning accuracy of radio aviation search and rescue is composed of two parts: ranging error and direction finding error. Direction finding error is easily affected by complex environmental interference, leading to a rapid increase in positioning error. To solve this problem, this work proposes a novelly method of using multi-point ranging information to improve direction finding accuracy. Firstly, virtual target positions are generated using direction finding estimation information. Then, a set of ranging sequences is constructed, and direction finding information is estimated using multi-point ranging information and airborne position information in the set. Subsequently, a method using GDOP metric to update the set of ranging sequences is proposed, which significantly reduces the computational complexity and storage unit of the algorithm while ensuring its accuracy. Finally, simulation results show that the proposed method can achieve high-precision direction finding performance in complex environments.

关键词： Accuracy Simulation signal processing algorithms Estimation Interference signal processing Distance measurement Robustness Trajectory Aircraft

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