arXiv - EE - Signal Processing最新文献_第7页

A White-Box Deep-Learning Method for Electrical Energy System Modeling Based on Kolmogorov-Arnold Network 基于 Kolmogorov-Arnold 网络的电能系统建模白盒深度学习方法

arXiv - EE - Signal Processing Pub Date : 2024-09-12 DOI: arxiv-2409.08044

Zhenghao Zhou, Yiyan Li, Zelin Guo, Zheng Yan, Mo-Yuen Chow

引用次数: 0

Electromagnetic Normalization of Channel Matrix for Holographic MIMO Communications 全息多输入多输出通信信道矩阵的电磁归一化

arXiv - EE - Signal Processing Pub Date : 2024-09-12 DOI: arxiv-2409.08080

Shuai S. A. Yuan, Li Wei, Xiaoming Chen, Chongwen Huang, Wei E. I. Sha

{"title":"Electromagnetic Normalization of Channel Matrix for Holographic MIMO Communications","authors":"Shuai S. A. Yuan, Li Wei, Xiaoming Chen, Chongwen Huang, Wei E. I. Sha","doi":"arxiv-2409.08080","DOIUrl":"https://doi.org/arxiv-2409.08080","url":null,"abstract":"Holographic multiple-input and multiple-output (MIMO) communications\u0000introduce innovative antenna array configurations, such as dense arrays and\u0000volumetric arrays, which offer notable advantages over conventional planar\u0000arrays with half-wavelength element spacing. However, accurately assessing the\u0000performance of these new holographic MIMO systems necessitates careful\u0000consideration of channel matrix normalization, as it is influenced by array\u0000gain, which, in turn, depends on the array topology. Traditional normalization\u0000methods may be insufficient for assessing these advanced array topologies,\u0000potentially resulting in misleading or inaccurate evaluations. In this study,\u0000we propose electromagnetic normalization approaches for the channel matrix that\u0000accommodate arbitrary array topologies, drawing on the array gains from\u0000analytical, physical, and full-wave methods. Additionally, we introduce a\u0000normalization method for near-field MIMO channels based on a rigorous dyadic\u0000Green's function approach, which accounts for potential losses of gain at near\u0000field. Finally, we perform capacity analyses under quasi-static, ergodic, and\u0000near-field conditions, through adopting the proposed normalization techniques.\u0000Our findings indicate that channel matrix normalization should reflect the\u0000realized gains of the antenna array in target directions. Failing to accurately\u0000normalize the channel matrix can result in errors when evaluating the\u0000performance limits and benefits of unconventional holographic array topologies,\u0000potentially compromising the optimal design of holographic MIMO systems.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Millimeter-Wave Integrated Silicon Devices: Active versus Passive -- The Eternal Struggle Between Good and Evil 毫米波集成硅器件：有源与无源 -- 善与恶的永恒斗争

arXiv - EE - Signal Processing Pub Date : 2024-09-12 DOI: arxiv-2409.08176

Michele Spasaro, Domenico Zito

{"title":"Millimeter-Wave Integrated Silicon Devices: Active versus Passive -- The Eternal Struggle Between Good and Evil","authors":"Michele Spasaro, Domenico Zito","doi":"arxiv-2409.08176","DOIUrl":"https://doi.org/arxiv-2409.08176","url":null,"abstract":"With the extreme scaling, active devices in both CMOS and BiCMOS technologies\u0000have reached outstanding ft/fmax, enabling an ever-increasing number of\u0000existing and emerging applications in the microwave and millimeter wave\u0000(mm-wave) frequency range. The increase in transistors ft/fmax has been so much\u0000significant that the performance of microwave and mm-wave ICs are limited\u0000mainly by losses in passive devices. In this paper, we address a discussion on\u0000qualitative and quantitative aspects that may help to further unveil the impact\u0000of such losses on the overall circuit performance and stimulate the adoption of\u0000effective loss-aware design methodologies. As example, we report the results\u0000related to the design of low power mm-wave low noise amplifiers (LNAs). Our\u0000results show how, in low power regime, the performances of mm-wave LNAs are\u0000dominated by losses in passive components. We also show how loss-aware design\u0000methodologies can mitigate the performance degradation due to passives,\u0000resulting as an important tool to get the full potential out of the active\u0000devices available today.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mental Stress Detection and Performance Enhancement Using FNIRS and Wrist Vibrator Biofeedback 利用 FNIRS 和腕部振动器生物反馈检测心理压力并提高绩效

arXiv - EE - Signal Processing Pub Date : 2024-09-12 DOI: arxiv-2409.08089

Anita Beigzadeh, Vahid Yazdnian, Kamaledin Setarehdan

{"title":"Mental Stress Detection and Performance Enhancement Using FNIRS and Wrist Vibrator Biofeedback","authors":"Anita Beigzadeh, Vahid Yazdnian, Kamaledin Setarehdan","doi":"arxiv-2409.08089","DOIUrl":"https://doi.org/arxiv-2409.08089","url":null,"abstract":"Any person in his/her daily life activities experiences different kinds and\u0000various amounts of mental stress which has a destructive effect on their\u0000performance. Therefore, it is crucial to come up with a systematic way of\u0000stress management and performance enhancement. This paper presents a\u0000comprehensive portable and real-time biofeedback system that aims at boosting\u0000stress management and consequently performance enhancement. For this purpose, a\u0000real-time brain signal acquisition device, a wireless vibration biofeedback\u0000device, and a software-defined program for stress level classification have\u0000been developed. More importantly, the entire system has been designed to\u0000present minimum time delay by propitiously bridging all the essential parts of\u0000the system together. We have presented different signal processing and feature\u0000extraction techniques for an online stress detection application. Accordingly,\u0000by testing the stress classification section of the system, an accuracy of 83%\u0000and a recall detecting the true mental stress level of 92% was achieved.\u0000Moreover, the biofeedback system as integrity has been tested on 20\u0000participants in the controlled experimental setup. Experiment evaluations show\u0000promising results of system performances, and the findings reveal that our\u0000system is able to help the participants reduce their stress level by 55% and\u0000increase their accuracy by 24.5%. It can be concluded from the observations\u0000that all primary premises on stress management and performance enhancement\u0000through reward learning are valid as well.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Efficient Learning of Balanced Signed Graphs via Iterative Linear Programming 通过迭代线性规划高效学习平衡符号图

arXiv - EE - Signal Processing Pub Date : 2024-09-12 DOI: arxiv-2409.07794

Haruki Yokota, Hiroshi Higashi, Yuichi Tanaka, Gene Cheung

{"title":"Efficient Learning of Balanced Signed Graphs via Iterative Linear Programming","authors":"Haruki Yokota, Hiroshi Higashi, Yuichi Tanaka, Gene Cheung","doi":"arxiv-2409.07794","DOIUrl":"https://doi.org/arxiv-2409.07794","url":null,"abstract":"Signed graphs are equipped with both positive and negative edge weights,\u0000encoding pairwise correlations as well as anti-correlations in data. A balanced\u0000signed graph has no cycles of odd number of negative edges. Laplacian of a\u0000balanced signed graph has eigenvectors that map simply to ones in a\u0000similarity-transformed positive graph Laplacian, thus enabling reuse of\u0000well-studied spectral filters designed for positive graphs. We propose a fast\u0000method to learn a balanced signed graph Laplacian directly from data.\u0000Specifically, for each node $i$, to determine its polarity $beta_i in\u0000{-1,1}$ and edge weights ${w_{i,j}}_{j=1}^N$, we extend a sparse inverse\u0000covariance formulation based on linear programming (LP) called CLIME, by adding\u0000linear constraints to enforce ``consistent\" signs of edge weights\u0000${w_{i,j}}_{j=1}^N$ with the polarities of connected nodes -- i.e.,\u0000positive/negative edges connect nodes of same/opposing polarities. For each LP,\u0000we adapt projections on convex set (POCS) to determine a suitable CLIME\u0000parameter $rho > 0$ that guarantees LP feasibility. We solve the resulting LP\u0000via an off-the-shelf LP solver in $mathcal{O}(N^{2.055})$. Experiments on\u0000synthetic and real-world datasets show that our balanced graph learning method\u0000outperforms competing methods and enables the use of spectral filters and graph\u0000convolutional networks (GCNs) designed for positive graphs on signed graphs.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Conformal Distributed Remote Inference in Sensor Networks Under Reliability and Communication Constraints 可靠性和通信约束条件下传感器网络中的共形分布式远程推理

arXiv - EE - Signal Processing Pub Date : 2024-09-12 DOI: arxiv-2409.07902

Meiyi Zhu, Matteo Zecchin, Sangwoo Park, Caili Guo, Chunyan Feng, Petar Popovski, Osvaldo Simeone

{"title":"Conformal Distributed Remote Inference in Sensor Networks Under Reliability and Communication Constraints","authors":"Meiyi Zhu, Matteo Zecchin, Sangwoo Park, Caili Guo, Chunyan Feng, Petar Popovski, Osvaldo Simeone","doi":"arxiv-2409.07902","DOIUrl":"https://doi.org/arxiv-2409.07902","url":null,"abstract":"This paper presents communication-constrained distributed conformal risk\u0000control (CD-CRC) framework, a novel decision-making framework for sensor\u0000networks under communication constraints. Targeting multi-label classification\u0000problems, such as segmentation, CD-CRC dynamically adjusts local and global\u0000thresholds used to identify significant labels with the goal of ensuring a\u0000target false negative rate (FNR), while adhering to communication capacity\u0000limits. CD-CRC builds on online exponentiated gradient descent to estimate the\u0000relative quality of the observations of different sensors, and on online\u0000conformal risk control (CRC) as a mechanism to control local and global\u0000thresholds. CD-CRC is proved to offer deterministic worst-case performance\u0000guarantees in terms of FNR and communication overhead, while the regret\u0000performance in terms of false positive rate (FPR) is characterized as a\u0000function of the key hyperparameters. Simulation results highlight the\u0000effectiveness of CD-CRC, particularly in communication resource-constrained\u0000environments, making it a valuable tool for enhancing the performance and\u0000reliability of distributed sensor networks.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Differences between Two Maximal Principal Strain Rate Calculation Schemes in Traumatic Brain Analysis with in-vivo and in-silico Datasets 利用体内和实验室数据集分析创伤性脑部时两种最大主应变率计算方案的差异

arXiv - EE - Signal Processing Pub Date : 2024-09-12 DOI: arxiv-2409.08164

Xianghao Zhan, Zhou Zhou, Yuzhe Liu, Nicholas J. Cecchi, Marzieh Hajiahamemar, Michael M. Zeineh, Gerald A. Grant, David Camarillo, Svein Kleiven

{"title":"Differences between Two Maximal Principal Strain Rate Calculation Schemes in Traumatic Brain Analysis with in-vivo and in-silico Datasets","authors":"Xianghao Zhan, Zhou Zhou, Yuzhe Liu, Nicholas J. Cecchi, Marzieh Hajiahamemar, Michael M. Zeineh, Gerald A. Grant, David Camarillo, Svein Kleiven","doi":"arxiv-2409.08164","DOIUrl":"https://doi.org/arxiv-2409.08164","url":null,"abstract":"Brain deformation caused by a head impact leads to traumatic brain injury\u0000(TBI). The maximum principal strain (MPS) was used to measure the extent of\u0000brain deformation and predict injury, and the recent evidence has indicated\u0000that incorporating the maximum principal strain rate (MPSR) and the product of\u0000MPS and MPSR, denoted as MPSxSR, enhances the accuracy of TBI prediction.\u0000However, ambiguities have arisen about the calculation of MPSR. Two schemes\u0000have been utilized: one (MPSR1) is to use the time derivative of MPS, and\u0000another (MPSR2) is to use the first eigenvalue of the strain rate tensor. Both\u0000MPSR1 and MPSR2 have been applied in previous studies to predict TBI. To\u0000quantify the discrepancies between these two methodologies, we conducted a\u0000comparison of these two MPSR methodologies across nine in-vivo and in-silico\u0000head impact datasets and found that 95MPSR1 was 5.87% larger than 95MPSR2, and\u000095MPSxSR1 was 2.55% larger than 95MPSxSR2. Across every element in all head\u0000impacts, MPSR1 was 8.28% smaller than MPSR2, and MPSxSR1 was 8.11% smaller than\u0000MPSxSR2. Furthermore, logistic regression models were trained to predict TBI\u0000based on the MPSR (or MPSxSR), and no significant difference was observed in\u0000the predictability across different variables. The consequence of misuse of\u0000MPSR and MPSxSR thresholds (i.e. compare threshold of 95MPSR1 with value from\u000095MPSR2 to determine if the impact is injurious) was investigated, and the\u0000resulting false rates were found to be around 1%. The evidence suggested that\u0000these two methodologies were not significantly different in detecting TBI.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Digital Twin for Autonomous Guided Vehicles based on Integrated Sensing and Communications 基于综合传感与通信的自主制导车辆数字孪生系统

arXiv - EE - Signal Processing Pub Date : 2024-09-12 DOI: arxiv-2409.08005

Van-Phuc Bui, Pedro Maia de Sant Ana, Soheil Gherekhloo, Shashi Raj Pandey, Petar Popovski

引用次数: 0

Quantum Inverse Fast Fourier Transform 量子反快速傅里叶变换

arXiv - EE - Signal Processing Pub Date : 2024-09-12 DOI: arxiv-2409.07983

Mayank Roy, Devi Maheswaran

引用次数: 0

Dequantization of a signal from two parallel quantized observations 从两个平行量化观测结果中对信号进行去量化

arXiv - EE - Signal Processing Pub Date : 2024-09-12 DOI: arxiv-2409.08071

Vojtěch Kovanda, Pavel Rajmic

引用次数: 0